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Sport Medicine

Cite as: Archiv EuroMedica. 2026. 16; 4. DOI 10.35630/2026/16/Iss.4.01

Received 20 July 2026;
Accepted 18 August 2026;
Published 21 August 2026

QUALITY MANAGEMENT IN RESISTANCE TRAINING PROGRAMS FOR OLDER ADULTS: A NARRATIVE REVIEW

Maciej Łabuś¹ , Aleksandra Skawińska¹ ,
Tomasz Wołoszczuk¹ , Zofia Graca¹ ,
Jakub Kołodziej¹ , Aleksandra Skowronek¹ ,
Julia Jeziorna¹ , Elżbieta Siudmak¹ ,
Agnieszka Sawina¹ , Adam Iwanicki¹

¹ Medical University of Silesia, Katowice, Poland

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  maciej.wojciech.labus@gmail.com

ABSTRACT

Background

Aging is associated with declines in muscle strength, muscle mass, and physical function, which increase the risks of falls, disability, and loss of independence. The effectiveness and safety of resistance training depend on both exercise prescription and program implementation.

Aim

This narrative review aimed to systematize the principal components of quality management in resistance training programs for older adults, summarize their effects on functional and health outcomes, and examine how program quality components are associated with effectiveness and safety.

Materials and methods

PubMed and Google Scholar were searched for English-language publications available through July 2026. The review considered randomized controlled trials, observational studies, systematic reviews, meta-analyses, clinical guidelines, position statements, and narrative reviews. Quality management was examined in relation to exercise prescription, program design, progression, monitoring, safety, adherence support, and wearable technologies. The evidence was synthesized thematically.

Results

Resistance training consistently improves muscle strength and physical function. Effects on muscle mass, balance, fall risk, and metabolic outcomes vary according to participant characteristics, program content, and intervention duration. Appropriate program organization includes individualized exercise and load selection, progressive overload, supervision of technique and safety, outcome monitoring, and adherence support. However, the available evidence does not identify a universally optimal protocol or establish the independent contribution of each quality component to effectiveness, safety, and health outcomes. Multicomponent programs may address several determinants of functional decline, although their effects cannot be attributed to resistance training alone. Wearable technologies may support monitoring, feedback, and individualized follow-up, but evidence concerning their accuracy during resistance exercise and their effects on adherence and clinical outcomes remains limited.

Conclusions

Resistance training improves muscle strength and physical function in older adults. Program quality requires individualized prescription, appropriate progression, safety supervision, outcome monitoring, and adherence support. Further long-term research is needed to determine the contribution of individual program components and the clinical value of wearable technologies in diverse older populations.

Keywords: dynapenia; sarcopenia; exercise prescription; functional capacity; wearable technology; physical independence

1. INTRODUCTION

Aging is associated with a progressive decline in functional capacity, including muscle strength, endurance, coordination, and flexibility [1,2]. These changes lead to difficulties in performing activities of daily living and increase the risk of loss of independence and disability [3]. Physical activity plays a crucial role in maintaining functional capacity and independence in older adults. In particular, regular participation in multicomponent exercise programs combining resistance, endurance, balance, and mobility training has been shown to be effective in improving muscle strength, mobility, balance, gait speed, muscle mass, and joint range of motion [3]. Resistance training plays an important role in the prevention and management of sarcopenia [4,5]. Falls rank as the second leading cause of fatal unintentional injuries globally, resulting in approximately 650,000 deaths, with older adults being particularly susceptible. Research indicates that resistance training can reduce the risk of falls associated with aging [6].

Resistance training represents an effective preventive strategy against numerous age-related chronic conditions, including type 2 diabetes, cardiovascular diseases, and cancer, and should be promoted as a key component of healthy aging [7]. The effectiveness of resistance training in older adults largely depends on program quality, including exercise selection, intensity, volume, progression, and adherence to safety guidelines. Optimizing these components is essential to maximize functional benefits, minimize injury risk, and ensure sustained engagement. Although the benefits of resistance training are well established, evidence addressing quality management strategies, including exercise prescription, monitoring, adherence, and wearable technologies, remains dispersed across different fields and has not been comprehensively synthesized. Therefore, a comprehensive review is warranted to support the design, monitoring, and implementation of high-quality resistance training programs for older adults.

2. AIM

The aim of this narrative review was to synthesize current evidence on quality management in resistance training programs for older adults and to identify the principal components required for their safe, individualized, and clinically relevant design, implementation, and monitoring.

Objectives

1. To identify and systematize the principal components of quality management in resistance training programs for older adults, including exercise prescription, program design, progression, monitoring, safety, adherence, and wearable technologies.
2. To summarize the effects of resistance training programs on muscle strength, muscle mass, physical function, balance, fall risk, and metabolic outcomes.
3. To examine the reported associations between individual components of program quality and the effectiveness, safety, and health outcomes of resistance training programs.

3. MATERIALS AND METHODS

This study was conducted as a narrative review to synthesize current evidence on quality management in resistance training programs for older adults.

For the purposes of this review, quality management was defined as the structured set of processes used to design, implement, monitor, evaluate, and adjust resistance training programs to ensure that they are individualized, safe, clinically relevant, and consistently delivered. This concept was operationalized through the following analytical domains: exercise selection and prescription; training frequency, intensity, volume, and progression; adaptation to health status and functional capacity; supervision of exercise technique and safety; monitoring of functional and health outcomes; adherence support; incorporation of functional, balance, and power exercises; and the use of wearable and mobile technologies.

For each domain, the review examined how it was addressed in the included publications and whether the authors reported relationships with muscle strength, muscle mass, physical function, balance, fall risk, metabolic outcomes, adverse events, or adherence. Quality management was used as an analytical framework for organizing and interpreting the evidence, rather than as a validated measurement scale. Because the included studies did not consistently evaluate individual program components as independent determinants of outcomes, no overall quality score was assigned, and causal effects were not attributed to individual components unless they had been directly investigated.

A literature search was performed using the PubMed and Google Scholar databases. Publications available up to July 2026 were considered, without restrictions on the year of publication. The main PubMed search formula was: ("resistance training" OR "strength training") AND ("older adults" OR aging) AND (sarcopenia OR "exercise prescription" OR "quality management" OR "functional exercise" OR "wearable technology" OR "physical activity monitoring" OR adherence). The same keywords were used in adapted combinations in Google Scholar. Additional relevant publications were identified by screening the reference lists of selected articles.

Only articles published in English were included. Studies were selected based on their relevance to the objectives of the review and included randomized controlled trials, observational studies, systematic reviews, meta-analyses, clinical practice guidelines, position statements, and other relevant review articles addressing resistance training, exercise prescription, functional performance, quality management, or wearable technologies in older adults. Editorials, conference abstracts, letters to the editor, and publications not directly related to the review topic were excluded.

Overall, 64 publications met the inclusion criteria and were synthesized narratively. The literature was organized into thematic categories corresponding to the review objectives, including age-related musculoskeletal decline and the health and functional outcomes of resistance training; program quality, including individualized exercise prescription, training parameters, progression, functional and balance exercises, monitoring, safety, and adherence; and the applications, measurement accuracy, and implementation barriers of wearable and mobile technologies.

Findings from different study designs were compared and synthesized narratively to provide a comprehensive overview of current evidence and its practical implications.

4. RESULTS

The review synthesized 64 publications, including randomized controlled trials, observational studies, systematic reviews, meta-analyses, clinical practice guidelines, and position statements. Findings are presented according to five thematic areas reflecting the objectives of the review.

4.1 Aging and Musculoskeletal Decline

The aging process is characterized by a progressive deterioration of skeletal muscle homeostasis, manifesting through two distinct yet interrelated phenomena: sarcopenia and dynapenia. Sarcopenia has been defined by the European Working Group on Sarcopenia in Older People (EWGSOP) as a progressive and generalized skeletal muscle disorder involving the accelerated loss of muscle mass and function. According to the updated EWGSOP2 diagnostic criteria published in 2019, the diagnosis of sarcopenia requires the presence of both low muscle strength and reduced muscle quantity or quality [8]. In contrast, dynapenia refers specifically to the age-related loss of muscle strength and power, independent of muscle mass, indicating that reductions in muscle strength are not fully explained by losses of muscle mass alone [9,10]. The pathophysiological mechanisms underlying sarcopenia and dynapenia are multifactorial and interconnected. At the cellular level, aging disrupts the equilibrium between anabolic and catabolic pathways of muscle protein metabolism, resulting in net muscle tissue loss [11]. Histological changes include reductions in both the size and number of muscle fibers, with preferential atrophy of type II (fast-twitch) fibers, intramuscular fat infiltration, and a decreased number of satellite cells [12]. Mitochondrial dysfunction and alterations in neuromuscular junction integrity further limit energy availability and muscle repair mechanisms [13]. At the molecular level, aging induces dysregulation of signaling cascades involving insulin-like growth factor 1 (IGF-1) and the mechanistic target of rapamycin (mTOR). Hormonal alterations, including diminished circulating levels of growth hormone, testosterone, and IGF-1, attenuate anabolic signaling and promote muscle atrophy [14]. Chronic low-grade inflammation (inflammaging), characterized by elevated levels of proinflammatory cytokines such as TNF-α, IL-6, and C-reactive protein, accelerates muscle protein degradation and impairs anabolic responses to exercise and nutritional stimuli [15, 16]. Age-related neurodegeneration and denervation of muscle fibers exacerbate muscle mass loss, particularly affecting fast-twitch fibers and reducing motor unit integrity [15].

The clinical consequences of sarcopenia and dynapenia are substantial and multidimensional. Sarcopenia has been associated with an increased risk of adverse health outcomes. A systematic review and meta-analysis reported an odds ratio of approximately 3.59 for mortality and 3.03 for functional decline among individuals with sarcopenia compared with those without sarcopenia. The association with mortality was more pronounced in older age groups. Sarcopenia has also been associated with an increased risk of falls, hospitalization, fractures, and poorer quality of life [17]. Loss of functional independence associated with sarcopenia and dynapenia is accompanied by increased nursing care requirements and a substantial economic burden on healthcare systems [13].

4.2 Benefits of Resistance Training in Older Adults

Resistance training improved muscle strength and mass among older adults across the included studies. A meta-analysis involving individuals aged 75 years and older demonstrated improvements in muscle strength, including among participants aged 80 years and above. Low-volume resistance training increased lean body mass and promoted muscle hypertrophy, whereas greater training volumes were associated with larger strength gains [20]. Furthermore, moderate-to-high-intensity circuit resistance training produced significant increases in both upper and lower-limb strength, as well as improvements in lean body mass in older populations [21,22]. These interventions also improved physical function and mobility among older adults. A systematic review demonstrated that resistance training increased 6-minute walk test distance, lower extremity strength, and gait speed in older adults with mobility limitations [23]. In individuals with sarcopenia and frailty syndrome, such programs significantly improved handgrip strength, lower-limb strength, agility, gait speed, postural stability, and overall functional performance [24]. Strength training was associated with improvements in metabolic parameters in older adults. In individuals with type 2 diabetes mellitus, resistance training improved insulin sensitivity and reduced fasting glucose concentrations, glycated hemoglobin levels, and HOMA-IR, while also attenuating systemic inflammation as measured by C-reactive protein levels [26]. Studies in healthy older adults reported reductions in total cholesterol, LDL cholesterol, glucose, insulin, and insulin resistance [27]. Resistance training has been associated with favorable effects on cardiovascular health and cardiovascular risk factors in adults with and without cardiovascular disease [34].

4.3 Concept of Quality Management in Exercise Programs

4.3.1 Exercise Program Design and Training Principles
Across the included publications, quality management was described as a systematic approach to the planning, implementation, and monitoring of exercise interventions. The FITT-VP model encompasses six parameters - frequency, intensity, time, type, volume, and progression - used to individualize exercise prescription [29]. Structured exercise prescriptions should be individualized and monitored in a manner comparable to other medical interventions, with consideration of dose-response relationships and the adaptations required to achieve specific outcomes [36]. Specificity and progressive overload are fundamental principles of resistance exercise prescription. Specificity refers to the principle that training adaptations are related to the training stimulus applied, whereas progressive overload involves increasing the training stimulus as adaptation occurs [30,31]. In practical resistance training prescription, the load may be increased by approximately 2-10% when an individual can perform one to two repetitions beyond the desired number at the current workload [31]. Periodized programs incorporate planned variation in training variables; however, current evidence indicates that periodization does not consistently influence resistance-training outcomes [30]. Guidelines also recommend multicomponent programs for older adults combining aerobic, resistance, balance, and flexibility training [32]. Multicomponent interventions incorporating cognitive tasks were associated with improvements in frailty-related outcomes, cognitive function, fall-related outcomes, and functional capacity. Guidance for healthy longevity recommends combining structured exercise with incidental or lifestyle-integrated physical activities [36].

4.3.2 Monitoring, Adherence, and Safety in Exercise Programs
Systematic monitoring and evaluation were consistently identified as components of exercise program quality. Functional capacity in older adults is commonly assessed using standardized instruments, including the Short Physical Performance Battery (SPPB), which evaluates balance, gait speed, and chair-stand performance; the 6-Minute Walk Test (6MWT), which assesses aerobic endurance and mobility; gait-speed measurement, which is used as an indicator of functional decline and mortality risk; and the Montreal Cognitive Assessment, which screens for cognitive impairment that may affect exercise participation and adherence. Changes in activities of daily living (ADL) performance may warrant further functional assessment. Exercise interventions should address functional capacity, ADL performance, independence, and quality of life [24].

Participant adherence was also identified as a component of exercise program quality. Fourteen factors relevant to adherence were identified: program characteristics, involvement of multidisciplinary professionals, supervision, technology, initial assessment of participant characteristics and barriers or facilitators, participant education, enjoyment and the absence of unpleasant experiences, integration into daily living, social support, communication and feedback, availability of progress information and monitoring, self-efficacy, an active participant role, and goal setting [25].

Safety was another component of exercise program quality. Injury-prevention strategies should be proportionate to exercise-related risks, as excessively restrictive approaches may discourage participation. Initial exercise intensity should be low and increased gradually. Musculoskeletal overuse injuries were identified as the most common adverse events and therefore constituted the primary focus of risk management. Sudden death during exercise was reported to be rare, while regular physical activity was associated with a reduction in this risk. For older adults, increases in exercise frequency and duration should precede increases in intensity to reduce the risk of overuse injuries [34].

4.4 Evidence-Based Resistance Training Exercises for Older Adults

4.4.1 Types of Resistance Exercises and Training Equipment
Resistance training in older adults can be performed using a variety of equipment modalities, including free weights such as dumbbells and barbells, weight machines, elastic resistance bands, and bodyweight exercises. A recent network meta-analysis encompassing 102 trials with 4,754 community-dwelling older adults found that all resistance-training modalities produced moderate-to-large effects on strength, including machine-based training (SMD = 1.34), free weights (SMD = 1.15), elastic bands (SMD = 0.93), mixed training (SMD = 0.88), and bodyweight exercises (SMD = 0.71) [28]. These effect estimates were derived relative to control conditions and should not be interpreted as evidence of superiority of one equipment modality over another. Consistent with this interpretation, the 2026 ACSM Position Stand found that equipment type did not consistently influence resistance-training outcomes in healthy adults [30]. According to the American Heart Association scientific statement, bodyweight exercises including push-ups and squats demonstrate comparable efficacy to machine-based or free weight training for improving muscular fitness. The statement also indicates that resistance training modality may be selected according to individual preferences, enjoyment, and practicality [34]. Current recommendations describe comprehensive resistance training programs as incorporating 8-10 exercises targeting the major muscle groups, including the chest press, shoulder press, triceps extension, biceps curl, lat pull-down, lower-back extension, abdominal crunch or curl-up, leg press or quadriceps extension, leg curl, and calf raise [29]. Additional guidance recommends strengthening both upper- and lower-body muscle groups, with particular emphasis on the lower limbs [32]. A meta-analysis by Zhao et al. demonstrated that resistance training improved handgrip strength, gait speed, and skeletal muscle index in older adults with sarcopenia, with subgroup analyses supporting elastic-band training as an effective modality [38]. Comparative studies examining multi-joint exercises alone (e.g., chest press, seated row) versus combined multi-joint and single-joint protocols (additionally incorporating biceps curls and triceps extensions) have demonstrated equivalent efficacy in improving muscular strength and endurance in older populations [18].

4.4.2 Resistance Training Parameters and Functional Exercises
An older-adult-specific position statement recommends progressing toward 2-3 sets of 1-2 multijoint exercises per major muscle group at approximately 70-85% of 1RM, performed 2-3 times per week [16]. The 2026 ACSM Position Stand, based on evidence from healthy adults aged ≥18 years, found that greater voluntary strength gains were associated with heavier loads (≥80% of 1RM), 2-3 sets, and a training frequency of ≥2 sessions per week [30]. These findings represent strength-focused evidence in healthy adults and should not be interpreted as a universal prescription for all older adults. For older adults for whom higher loads are initially unsuitable, lower-intensity resistance training may be considered, with intensity adjusted according to clinical status, baseline functional capacity, and exercise tolerance [16,34]. A dose-response meta-analysis by Borde et al. identified training parameters associated with greater strength gains in healthy older adults: two sessions per week, 2-3 sets per exercise, 7-9 repetitions per set, an intensity of 70-79% of 1RM, and approximately 60 seconds of rest between sets [39]. These findings should not be interpreted as a universally optimal regimen.

Functional exercises integrated into everyday activities represent an alternative approach to conventional exercise programs for older adults. The Lifestyle-integrated Functional Exercise (LiFE) program incorporates individualized balance and lower-limb strengthening activities into habitual daily routines using situational and environmental cues, with progressive increases in task difficulty as functional capacity improves. A randomized controlled trial demonstrated that this approach improved static balance, ankle strength, functional performance, and participation, while reducing the rate of falls compared with a gentle exercise control program [33]. Yoshiko and Watanabe demonstrated that a home-based squat training protocol consisting of four sets of 35 repetitions performed three times per week for 12 weeks significantly improved lower limb function and performance in physical function tests related to activities of daily living, with improvements observed regardless of squat depth [41].

4.4.3 Power Training
The ability to generate high muscular power declines progressively with age, and the reduction in power is typically greater than the decline in maximal muscle strength [16]. Power training involves performing the concentric phase at a high intended velocity while maintaining control during the eccentric phase. The 2026 ACSM Position Stand found that power gains were enhanced by moderate loads of approximately 30-70% of 1RM and by resistance training performed with a fast concentric phase [30]. Evidence from a systematic review and meta-analysis published in JAMA Network Open indicates that power training leads to a modest improvement in physical function compared with traditional strength training in healthy older adults, although the certainty of evidence was low [42].

4.4.4 Balance Exercises as a Program Component
Falls in older adults represent a leading cause of chronic disability and loss of functional independence [34]. Devries and Giangregorio emphasized that resistance exercises targeting the major muscle groups at an intensity of 6-12 repetition maximum, combined with challenging balance exercises, should be performed at least twice weekly. Exercise selection should align with patient-specific goals and movements performed during daily activities, reflecting the principle of task specificity, while balance exercises should be tailored to individual ability levels and specific balance deficits requiring improvement [40]. A comprehensive Cochrane systematic review encompassing 108 randomized controlled trials with over 23,000 participants demonstrated that exercise programs reduced the rate of falls by 23% compared with control interventions. Programs combining multiple exercise types - most commonly balance and functional exercises with resistance exercises - produced the largest reduction in fall rates: 34% (rate ratio = 0.66; 95% CI, 0.50-0.88) [43]. A subsequent JAMA review confirmed these findings, reporting that participants in exercise interventions experienced 655 falls per 1000 patient-years compared with 850 falls per 1000 patient-years in control groups. Meta-regression analyses indicated that interventions providing at least 50 hours of training were associated with greater reductions in falls [44]. Programs associated with the largest reductions in falls included exercises that improved leg strength and progressively challenged balance [45].

Selected recommendations and findings on resistance training prescription and program design in older adults are summarized in Table 1.

4.5 Wearable and Mobile Technologies Supporting Physical Activity and Resistance Training in Older Adults

The reported applications and findings concerning wearable devices and mobile technologies supporting physical activity and resistance exercise among older adults are summarized in Table 2.

4.5.1 Efficacy of Wearable Devices in Promoting Physical Activity
Wearable devices, including smartwatches and fitness bands, have been evaluated as tools for supporting physical activity engagement among older adults. A systematic review and meta-analysis conducted by Li et al., encompassing 23 studies with 4,566 participants, demonstrated that wearable activity tracker-based interventions significantly increased physical activity duration (SMD=0.28; 95% CI 0.10-0.47) and daily step counts (SMD=0.58; 95% CI 0.33-0.83) compared with standard care [46]. An earlier systematic review by Oliveira et al. reported that activity-tracker interventions increased daily step counts by an average of 1,558 steps (95% CI, 1,099-2,018) and improved mobility outcomes (SMD = 0.61; 95% CI, 0.31-0.90) [47]. An investigation by Zhang et al. conducted among older adults (mean age 85.4 years) residing in retirement communities demonstrated that participants utilized the activity tracker on 97.5% of measurement days and achieved a mean increase of 900 steps daily. The devices were perceived as acceptable, useful, and easy to operate, with participants reporting enhanced self-awareness and motivation for physical activity [48].

4.5.2 Wearable Technology for Resistance Training Monitoring
A 2026 meta-analysis by Li et al. reported effect estimates favoring exercise interventions incorporating wearable electronic devices for lower-limb strength (SMD = -0.60; 95% CI, -1.15 to -0.05) and balance (SMD = -0.43; 95% CI, -0.81 to -0.06) in older adults. In this meta-analysis, effect directions were harmonized a priori across outcome measures. Negative SMD/MD values were defined as improvement for outcomes in which lower values indicated better status; for outcomes in which higher values represented improvement, data were entered so that improved performance corresponded to the same direction across studies. Therefore, the negative pooled SMDs reported for lower-limb strength and balance represented effects favoring the intervention. Exploratory subgroup analyses reported larger effect estimates for interventions delivered once weekly, with sessions lasting 10-45 minutes and intervention periods of 8-12 weeks; however, these subgroup findings were based on small numbers of studies and should be interpreted cautiously [49]. Ferrari et al. conducted a 6-month study of home-based resistance training using an inertial sensor and a dedicated tablet device. The intervention was feasible, no adverse events were recorded, and improvements were observed in gait parameters and maximal lower-limb force. During the first three months, 61% of participants completed the target of three sessions per week; adherence declined during the subsequent three months [50].

4.5.3 Mobile Applications for Resistance Training
A review by McGarrigle et al. identified 13 applications and 24 websites supporting independent performance of strength and balance exercises by older adults. Based on the available evidence, quality metrics, and incorporated behavior-change techniques, four applications and six websites were recommended for older adults wishing to exercise independently at home [51]. A 2023 review by Soto-Bagaria et al. analyzed over 2,800 applications, of which only 17 met inclusion criteria for older adults with frailty syndrome. Of these applications, only Vivifrail was supported by published scientific evidence [52]. Netz et al. developed a smartphone platform for remote motor fitness assessment and generation of personalized exercise programs utilizing artificial intelligence. A study involving 239 participants demonstrated significant improvements in dynamic balance, arm flexibility, and arm strength in the group receiving personalized exercises compared with control groups [53]. The LEAN system developed by Coates and Wahlström is a resistance-training analysis application for iPhone and Apple Watch that provides machine-learning-based form analysis, real-time repetition counting, and repetition-level range-of-motion measurement [54].

4.5.4 Technologies for Resistance Training Intensity Measurement
The 2025 ACSM and ESSA expert consensus statement indicates that resistance-training intensity is determined not only by external load but also by proximity to neuromuscular failure, commonly expressed as repetitions in reserve (RIR) [55]. Perceived exercise intensity may also be monitored using the OMNI Resistance Exercise Scale (OMNI-RES), a rating-of-perceived-exertion scale used during resistance exercise [19]. A 2025 systematic review by Brennan et al. evaluated the classification performance of wrist-worn inertial measurement units (IMUs) for resistance exercises, including lower-extremity movements [56]. Conger et al. reported that a wrist-worn triaxial accelerometer classified 12 resistance exercises with 78-85% accuracy [57]. Pernek et al. developed a system based on a network of wearable accelerometers and smartphones that recognizes exercise type with approximately 85% accuracy and predicts intensity with 6% error [58].

4.5.5 Barriers and Challenges in Technology Adoption Among Older Adults
The American Heart Association statement associated lower smartphone use among adults aged over 70 years with visual limitations and reduced motor coordination. Additional cognitive barriers included reduced spatial working memory, slower information processing, and negative responses to errors [59]. A systematic review by Bertolazzi et al. identified five principal domains of barriers and facilitators: demographic-socioeconomic factors, health-related factors, dispositional factors, technological factors, and social factors. Insufficient technological skills, beliefs about consequences, and difficulties involving memory, attention, and decision-making were among the most frequently identified barriers [60,61]. A 2025 review by Tacca et al. found limited alignment between the reported preferences of older adults and the design and evaluation of fitness technologies. None of the 43 analyzed studies achieved a score of 3 or higher across all six evaluation factors (lifestyle compatibility, similarity to experiences, dignity and independence, privacy concerns, social support, emotions) [62].

4.5.6 Validation and Accuracy of Wearable Devices in Older Adults
A validation study by Kastelic et al. evaluated three consumer-grade activity trackers (Polar Vantage M, Garmin Vivoactive 4s, Garmin Vivosport) in older adults (mean age, 74 ± 5 years). Both Garmin devices demonstrated a mean absolute percentage error below 20% and an intraclass correlation coefficient above 0.90 for step-count measurement. Mean absolute percentage error for sleep time was below 10% for all tested trackers [63]. Beauchamp et al. demonstrated that the TicWatch Pro 3 Ultra GPS smartwatch was comparable with the Qstarz reference device across the assessed trip-related parameters and was capable of distinguishing passive and active transportation modes [64].

5. DISCUSSION

5.1 Principal findings and clinical relevance

This review demonstrates that resistance training remains one of the most effective non-pharmacological interventions for preserving functional capacity and mitigating age-related musculoskeletal decline in older adults [7,16,20,23,24,26].

The evidence consistently indicates that appropriately prescribed resistance exercise improves muscle strength, physical performance, metabolic health, and functional independence while reducing factors associated with frailty and fall risk [6,20-24,26,28,35,38].

The findings also support integrating resistance training with functional exercises, balance training, and power-oriented movements [33,36,40,42,43].

Wearable technologies and mobile health applications may complement conventional exercise delivery by facilitating monitoring and improving adherence [46-51]. Collectively, these findings support an integrated approach combining individualized exercise prescription, systematic progression, monitoring, safety, adherence support, and technological strategies [16,36,37,46,50,51].

5.2 Interpretation of current evidence

The agreement across systematic reviews and meta-analyses regarding the benefits of resistance training, despite variability in exercise protocols, strengthens confidence that it should be considered a fundamental component of exercise prescription for older adults [20,23,24,28,35,38].

Greater variation exists regarding the optimal training prescription. While international recommendations generally advocate moderate-to-high intensity resistance exercise performed two to three times weekly, individual studies propose different combinations of training frequency, intensity, volume, and repetition ranges [16,31,34,36].

Dose-response analyses identify relatively narrow intensity ranges that maximize strength gains, whereas professional guidelines provide broader recommendations to accommodate clinical heterogeneity [16,31,36,39]. These differences likely reflect variation in participant characteristics, baseline functional capacity, intervention duration, and study methodology rather than conflicting evidence [20,28,35,38,39]. Consequently, individualized exercise prescription remains more appropriate than adherence to a single standardized protocol [16,36,37].

The present review also highlights the growing emphasis on muscle function rather than muscle mass as the principal therapeutic target [8,12,15]. Earlier approaches to sarcopenia focused predominantly on preserving skeletal muscle quantity. Contemporary evidence increasingly recognizes muscle strength and physical performance as stronger predictors of disability, falls, hospitalization, and mortality [8,9,12,15].

Improvements in functional outcomes frequently exceed changes in lean muscle mass [5,20,35,38]. These observations reinforce the importance of selecting clinically meaningful functional outcomes when evaluating exercise interventions.

According to the EWGSOP2 criteria, low muscle strength indicates probable sarcopenia, low muscle quantity or quality confirms the diagnosis, and low physical performance indicates severe sarcopenia [8].

The additional benefits reported when resistance exercise is combined with balance, mobility, and functional exercises may reflect the multifactorial nature of frailty, falls, and disability [33,36,40,43-45].

These conditions involve interactions between muscular weakness, impaired balance, reduced mobility, and age-related physiological decline [24,33,43-45]. Multicomponent interventions may therefore be better suited to address multiple determinants of functional independence than isolated strength training [33,36,43].

5.3 Wearable technologies: promising but evolving evidence

The incorporation of wearable technologies represents a rapidly developing area identified in this review. Across the reviewed studies, wearable devices were used to monitor physical activity and provide feedback. Some interventions reported improvements in physical activity, participant engagement, or adherence, but the findings were not uniform, and evidence concerning self-management remains limited [46,48,50,51]. These findings suggest that digital technologies may support program monitoring by providing objective measures of exercise participation and enabling more individualized follow-up outside supervised clinical environments [46,50].

Despite these encouraging findings, several limitations remain. The available evidence largely concerns relatively short interventions involving community-dwelling older adults with comparatively preserved functional capacity [46,48,50]. Consequently, the effectiveness of wearable technologies among frail individuals, institutionalized populations, or patients with significant cognitive impairment remains insufficiently investigated [46,51,52].

Some consumer devices demonstrate acceptable validity and reliability for selected measures of general physical activity, but their accuracy varies according to the device, measured outcome, population, and conditions of use [63,64]. Considerably fewer studies have evaluated wearable technologies specifically during resistance training. Current evidence does not establish reliable measurement of all relevant variables, including exercise technique, external load, movement quality, and proximity to muscular fatigue [54,56].

An additional consideration concerns technology adoption itself. Studies included in this review identify barriers related to digital literacy, cognitive function, sensory impairment, and usability [51,60,61]. These observations suggest that successful implementation depends not only on technological capabilities but also on the development of user-centered systems adapted to the specific needs of older adults. Therefore, wearable technologies should currently be considered supportive tools that complement, rather than replace, professional supervision and individualized clinical assessment [50,51].

5.4 Quality and heterogeneity of the available evidence

Although the overall direction of evidence supports resistance training, the reviewed literature demonstrates considerable methodological heterogeneity. Differences in participant age, health status, diagnostic criteria for sarcopenia or frailty, intervention duration, exercise modalities, progression models, and outcome measures complicate direct comparisons between studies. Such variability also contributes to the heterogeneity reported in published meta-analyses [20,24,28].

An additional methodological challenge concerns the diversity of resistance training protocols. Studies differ substantially in exercise selection, training intensity, supervision, progression strategies, and adherence monitoring [16,36,39]. Consequently, although the effectiveness of resistance training is supported by the available evidence, identifying a universally optimal exercise prescription remains difficult. Instead, current recommendations support individualized programming based on functional status, clinical characteristics, exercise tolerance, and patient-specific goals [16,36,37].

The reviewed literature is further characterized by relatively limited long-term follow-up. Most intervention studies evaluate outcomes over periods ranging from several weeks to several months, providing limited information regarding the durability of exercise-induced adaptations [20,24,35]. Long-term maintenance of muscle strength, adherence, and functional independence therefore remains less well documented than short-term physiological improvements.

5.5 Future research

The findings of this review identify several priorities for future investigation. Greater methodological standardization of resistance training protocols would facilitate comparisons across studies and strengthen future evidence syntheses. Longitudinal randomized trials with extended follow-up are needed to determine whether improvements in muscle strength translate into sustained reductions in disability, institutionalization, hospitalization, and healthcare utilization [20,24,35].

Future research should also evaluate resistance training in more diverse populations, including very old adults, individuals with multimorbidity, frailty, or cognitive impairment, and residents of long-term care facilities. Such studies would improve the generalizability of current recommendations [24,35].

Finally, additional research is required to establish the clinical effectiveness of wearable technologies specifically within resistance training programs. Future investigations should evaluate exercise adherence, cost-effectiveness, usability, long-term engagement, and integration into routine healthcare systems [46,50,51]. The development of personalized exercise programs supported by digital health technologies represents a promising direction, although robust clinical evidence remains necessary before widespread implementation can be recommended [50,51,56].

Implementation research should also evaluate strategies for integrating evidence-based, high-quality resistance training programs into routine clinical and community care while maintaining effective monitoring, progression, and long-term adherence [36,37,51].

Limitations

This narrative review has several limitations. The literature search and study selection were not systematic, and the methodological quality and risk of bias of the included publications were not assessed using standardized tools. The included studies differed in population characteristics, training protocols, intervention duration, outcome measures, and types of digital technology, which limits direct comparison of their findings. Furthermore, some studies of wearable technologies evaluated technical capabilities in populations not restricted to older adults; therefore, these findings cannot be directly generalized to older populations.

6. Conclusions

Resistance training improves muscle strength and physical function in older adults. Its effects on muscle mass, balance, fall risk, and metabolic outcomes depend on participant characteristics, program content, and intervention duration.

The principal components of properly organized training programs include individualized selection of exercises and training loads, progressive increases in intensity, supervision of exercise technique and safety, outcome monitoring, and adherence support. Programs should be adapted to individual health status, functional capacity, and exercise tolerance. The available evidence does not allow identification of a single optimal protocol or confirmation of the independent effects of each of these components on effectiveness and clinical outcomes.

Multicomponent programs that include resistance, functional, balance, mobility, and power exercises may address several determinants of functional decline. However, the outcomes of such programs cannot be attributed exclusively to resistance training.

Wearable devices and mobile applications may support physical activity monitoring, feedback, and individualized follow up. Evidence regarding their accuracy during resistance training and their effects on adherence and clinical outcomes remains limited. Long term studies involving older adults with frailty or cognitive impairment and residents of long term care facilities are needed.

DISCLOSURE

Authors' contributions

Conceptualization: Maciej Łabuś, Aleksandra Skawińska, Tomasz Wołoszczuk, Elżbieta Siudmak, Aleksandra Skowronek, Jakub Kołodziej, Julia Jeziorna, Adam Iwanicki, Agnieszka Sawina, Zofia Graca. Methodology: Maciej Łabuś, Aleksandra Skawińska, Aleksandra Skowronek, Elżbieta Siudmak, Zofia Graca. Formal analysis: Maciej Łabuś, Julia Jeziorna, Aleksandra Skawińska, Adam Iwanicki, Agnieszka Sawina. Investigation: Maciej Łabuś, Aleksandra Skowronek, Agnieszka Sawina. Writing - original draft: Aleksandra Skawińska, Tomasz Wołoszczuk, Jakub Kołodziej. Writing - review and editing: Aleksandra Skawińska, Maciej Łabuś, Zofia Graca. Supervision: Aleksandra Skawińska, Elżbieta Siudmak, Julia Jeziorna, Adam Iwanicki. Funding acquisition: Not applicable.

All authors have read and approved the final version of the manuscript.

Funding

The article received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflict of Interest Statement

The authors declare no conflicts of interest.

Use of AI

Artificial intelligence-based language assistance was employed in the preparation of this manuscript. ChatGPT (OpenAI) was used to improve grammar and enhance the clarity and quality of scientific writing. All revisions were carefully reviewed by the authors, who approved the final manuscript and accepted full responsibility for its content.

REFERENCES

1. Riebe D, Blissmer BJ, Greaney ML, Ewing Garber C, Lees FD, Clark PG. The relationship between obesity, physical activity, and physical function in older adults. Journal of Aging and Health. 2009 Nov 6;21(8):1159-78. https://doi.org/10.1177/0898264309350076
2. Donat Tuna H, Ozcan Edeer A, Malkoc M, Aksakoglu G. Effect of age and physical activity level on functional fitness in older adults. European review of Aging and physical activity. 2009 Oct;6(2):99-106. https://doi.org/10.1007/s11556-009-0051-z
3. Milanović Z, Jorgić B, Trajković N, Sporis G, Pantelić S, James N. Age-related decrease in physical activity and functional fitness among elderly men and women. Clinical interventions in Aging. 2013 May;8(1):549. https://doi.org/10.2147/CIA.S44112
4. Chodzko-Zajko WJ, Proctor DN, Fiatarone Singh MA, Minson CT, Nigg CR, Salem GJ, et al. Exercise and physical activity for older adults. Medicine & Science in Sports & Exercise. 2009 Jul;41(7):1510-30. https://doi.org/10.1249/MSS.0b013e3181a0c95c
5. Vikberg S, Sörlén N, Brandén L, Johansson J, Nordström A, Hult A, et al. Effects of resistance training on functional strength and muscle mass in 70-year-old individuals with pre-sarcopenia: A randomized controlled trial. Journal of the American Medical Directors Association. 2019 Jan;20(1):28-34. https://doi.org/10.1016/j.jamda.2018.09.011
6. Claudino JG, Afonso J, Sarvestan J, Lanza MB, Pennone J, Filho CAC, et al. Strength training to prevent falls in older adults: A systematic review with meta-analysis of randomized controlled trials. Journal of Clinical Medicine. 2021 Jul 20;10(14):3184. https://doi.org/10.3390/jcm10143184
7. Mcleod JC, Stokes T, Phillips SM. Resistance exercise training as a primary countermeasure to age-related chronic disease. Frontiers in physiology. 2019 Jun 6;10. https://doi.org/10.3389/fphys.2019.00645
8. Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, et al. Sarcopenia: Revised european consensus on definition and diagnosis. Age and ageing. 2019 Jan 1;48(1):16-31. https://doi.org/10.1093/ageing/afy169
9. Manini TM, Clark BC. Dynapenia and aging: An update. The journals of Gerontology: Series a. 2011 Mar 28;67A(1):28-40. https://doi.org/10.1093/gerona/glr010
10. Kalyani RR, Corriere M, Ferrucci L. Age-related and disease-related muscle loss: The effect of diabetes, obesity, and other diseases. The lancet Diabetes & endocrinology. 2014 Oct 1;2(10):819-29. https://doi.org/10.1016/S2213-8587(14)70034-8
11. Nishikawa H, Fukunishi S, Asai A, Yokohama K, Nishiguchi S, Higuchi K. Pathophysiology and mechanisms of primary sarcopenia (review). International journal of Molecular medicine. 2021 Jun 25;48(2). https://doi.org/10.3892/ijmm.2021.4989
12. Cruz-Jentoft AJ, Sayer AA. Sarcopenia. The Lancet. 2019 Jun;393(10191):2636-46. https://doi.org/10.1016/S0140-6736(19)31138-9
13. Huang Y, Wang C, Cui H, Sun G, Qi X, Yao X. Mitochondrial dysfunction in age-related sarcopenia: Mechanistic insights, diagnostic advances, and therapeutic prospects. Frontiers in cell and developmental biology. 2025 Oct 3;13:1590524-4. https://doi.org/10.3389/fcell.2025.1590524
14. Priego T, Martín AI, González-Hedström D, Granado M, López-Calderón A. Role of hormones in sarcopenia. Vitamins and hormones. 2021;115:535-70. https://doi.org/10.1016/bs.vh.2020.12.021
15. Tieland M, Trouwborst I, Clark BC. Skeletal muscle performance and ageing. Journal of Cachexia, sarcopenia and muscle. 2017 Nov 19;9(1):3-19. https://doi.org/10.1002/jcsm.12238
16. Fragala MS, Cadore EL, Dorgo S, Izquierdo M, Kraemer WJ, Peterson MD, et al. Resistance training for older adults: Position statement from the national strength and conditioning association. Journal of strength and conditioning research. 2019 Aug;33(8):2019-52. https://doi.org/10.1519/JSC.0000000000003230
17. Beaudart C, Zaaria M, Pasleau F, Reginster JY, Bruyère O. Health Outcomes of Sarcopenia: A Systematic Review and Meta-Analysis. Wright JM, editor. PLOS ONE. 2017 Jan 17;12(1):e0169548. https://doi.org/10.1371/journal.pone.0169548
18. Bezerra E de S, Moro ARP, Orssatto LB da R, da Silva ME, Willardson JM, Simão R. Muscular performance and body composition changes following multi-joint versus combined multi- and single-joint exercises in aging adults. Applied Physiology, Nutrition, and Metabolism. 2018 June;43(6):602-8. https://doi.org/10.1139/apnm-2017-0655
19. Gearhart RF, Lagally KM, Riechman SE, Andrews RD, Robertson RJ. Strength tracking using the OMNI resistance exercise scale in older men and women. Journal of Strength and Conditioning Research. 2009 May;23(3):1011-5. https://doi.org/10.1519/JSC.0b013e3181a2ec41
20. Régis Radaelli, Rech A, Molinari T, Markarian AM, Petropoulou M, Urs Granacher, et al. Effects of resistance training volume on physical function, lean body mass and lower-body muscle hypertrophy and strength in older adults: A systematic review and network meta-analysis of 151 randomised trials. Sports medicine. 2024 Oct 15;. https://doi.org/10.1007/s40279-024-02123-z
21. Hu C, Xia Y, Zeng D, Ye M, Mei T. Effect of resistance circuit training on comprehensive health indicators in older adults: A systematic review and meta-analysis. Scientific reports. 2024 Apr 17;14(1):8823. https://doi.org/10.1038/s41598-024-59386-9
22. Marcos-Pardo PJ, Orquin-Castrillón FJ, Gea-García GM, Menayo-Antúnez R, González-Gálvez N, Vale RG de S, et al. Effects of a moderate-to-high intensity resistance circuit training on fat mass, functional capacity, muscular strength, and quality of life in elderly: A randomized controlled trial. Scientific reports. 2019 May 24;9(1). https://doi.org/10.1038/s41598-019-44329-6
23. Prevett C, Moncion K, Phillips S, Richardson J, Tang A. The role of resistance training in mitigating risk for mobility disability in community-dwelling older adults: A systematic review and meta-analysis. Archives of Physical medicine and rehabilitation. 2022 Apr;. https://doi.org/10.1016/j.apmr.2022.04.002
24. Talar K, Hernández-Belmonte A, Vetrovsky T, Steffl M, Kałamacka E, Courel-Ibáñez J. Benefits of resistance training in early and late stages of frailty and sarcopenia: A systematic review and meta-analysis of randomized controlled studies. Journal of Clinical Medicine. 2021 Apr 12;10(8):1630. https://doi.org/10.3390/jcm10081630
25. Collado-Mateo D, Lavín-Pérez AM, Peñacoba C, Del Coso J, Leyton-Román M, Luque-Casado A, et al. Key Factors Associated with Adherence to Physical Exercise in Patients with Chronic Diseases and Older Adults: An Umbrella Review. International Journal of Environmental Research and Public Health. 2021;18(4). https://doi.org/10.3390/ijerph18042023
26. Wang J, Fan S, Wang J. Resistance training enhances metabolic and muscular health and reduces systemic inflammation in middle-aged and older adults with type 2 diabetes: A meta-analysis. Diabetes research and clinical practice. 2025 Oct 15;229:112941. https://doi.org/10.1016/j.diabres.2025.112941
27. Williams A D, Almond J, Kiran D.K. Ahuja, Beard DC, Robertson IK, Ball MJ. Cardiovascular and metabolic effects of community based resistance training in an older population. Journal of science and medicine in sport. 2011 Mar 29;14(4):331-7. https://doi.org/10.1016/j.jsams.2011.02.011
28. Wiedenmann T, Held S, Morat T, Rappelt L, Isenmann E, Berndsen E, et al. The effects of Different resistance training modalities on muscle strength in community-dwelling older adults: A network meta-analysis. Gerontology. 2025;71(7):576-88. https://doi.org/10.1159/000546346
29. Fletcher GF, Ades PA, Kligfield P, Arena R, Balady GJ, Bittner VA, et al. Exercise standards for Testing and training. Circulation. 2013 Aug 20;128(8):873-934. https://doi.org/10.1161/cir.0b013e31829b5b44
30. Currier BS, D'Souza AC, Fiatarone Singh MA, Lowisz CV, Rawson ES, Schoenfeld BJ, et al. American College of Sports Medicine Position Stand. Resistance Training Prescription for Muscle Function, Hypertrophy, and Physical Performance in Healthy Adults: An Overview of Reviews. Med Sci Sports Exerc. 2026;58(4):851-872. https://doi.org/10.1249/MSS.0000000000003897
31. American College of Sports Medicine. Progression models in resistance training for healthy adults. Medicine & Science in Sports & Exercise. 2009 Mar;41(3):687-708. https://doi.org/10.1249/mss.0b013e3181915670
32. Cress ME, Buchner DM, Prohaska T, Rimmer J, Brown M, Macera C, et al. Physical activity programs and behavior counseling in Older adult populations. Medicine & Science in Sports & Exercise. 2004 Nov;36(11):1997-2003. https://doi.org/10.1249/01.mss.0000145451.08166.97
33. Clemson L, Fiatarone Singh MA, Bundy A, Cumming RG, Manollaras K, O’Loughlin P, et al. Integration of balance and strength training into daily life activity to reduce rate of falls in older people (the LiFE study): Randomised parallel trial. BMJ. 2012 Aug 7;345(aug07 1):e4547-7. https://doi.org/10.1136/bmj.e4547
34. Paluch AE, Boyer WR, Franklin BA, Laddu D, Lobelo F, Lee D, et al. Resistance exercise training in individuals with and without cardiovascular disease: 2023 Update: A scientific statement from the American heart association. Circulation. 2023 Dec 7;149(3). https://doi.org/10.1161/CIR.0000000000001189
35. Grgic J, Garofolini A, Orazem J, Sabol F, Schoenfeld BJ, Pedisic Z. Effects of Resistance training on muscle size and strength in very elderly adults: A systematic review and Meta-Analysis of Randomized controlled trials. Sports medicine. 2020 Aug 1;50. https://doi.org/10.1007/s40279-020-01331-7
36. Izquierdo M, de Souto Barreto P, Arai H, Bischoff-Ferrari HA, Cadore EL, Cesari M, et al. Global consensus on optimal exercise recommendations for enhancing healthy longevity in older adults (icfsr). The journal of Nutrition, health and aging. 2025 Jan 1;29(1):100401. https://doi.org/10.1016/j.jnha.2024.100401
37. Baptista FM, Andias R, Rocha NP, Silva AG. A practice guide for physical therapists prescribing physical exercise for older adults. Journal of aging and physical activity. 2024 Nov;32(6):1-13. https://doi.org/10.1123/japa.2023-0283
38. Zhao H, Cheng R, Song G, Teng J, Shen S, Fu X, et al. The effect of resistance training on the rehabilitation of elderly patients with sarcopenia: A meta-analysis. International journal of Environmental research and public health. 2022 Jan 1;19(23):15491. https://doi.org/10.3390/ijerph192315491
39. Borde R, Hortobágyi T, Granacher U. Dose-Response relationships of resistance training in healthy old adults: A systematic review and meta-analysis. Sports medicine. 2015 Sep 29;45(12):1693-720. https://doi.org/10.1007/s40279-015-0385-9
40. Devries MC, Giangregorio L. Using the specificity and overload principles to prevent sarcopenia, falls and fractures with exercise. Bone. 2023 Jan;166(116573):116573. https://doi.org/10.1016/j.bone.2022.116573
41. Yoshiko A, Watanabe K. Impact of home-based squat training with two-depths on lower limb muscle parameters and physical functional tests in older adults. Scientific reports. 2021 Mar 25;11(1):6855. https://doi.org/10.1038/s41598-021-86030-7
42. Balachandran AT, Steele J, Angielczyk D, Belio M, Schoenfeld BJ, Quiles N, et al. Comparison of Power training vs traditional strength training on physical function in older adults. JAMA network open. 2022 May 11;5(5):e2211623. https://doi.org/10.1001/jamanetworkopen.2022.11623
43. Sherrington C, Fairhall NJ, Wallbank GK, Tiedemann A, Michaleff ZA, Howard K, et al. Exercise for preventing falls in older people living in the community. Cochrane database of systematic reviews. 2020 Jan 31;1(1):CD012424. https://doi.org/10.1002/14651858.CD012424.pub2
44. Colón-Emeric CS, McDermott CL, Lee DS, Berry S D. Risk assessment and prevention of falls in older community-dwelling adults: A review. JAMA. 2024;331(16). https://doi.org/10.1001/jama.2024.1416
45. Ganz DA, Latham NK. Prevention of falls in community-dwelling older adults. New England Journal of Medicine. 2020 Feb 20;382(8):734-43. https://doi.org/10.1056/NEJMcp1903252
46. Li R, Li Y, Wang L, Li L, Fu C, Hu D, et al. Wearable activity tracker-based interventions for physical activity, body composition, and physical function among community-dwelling older adults: Systematic review and meta-analysis of randomized controlled trials. Journal of Medical internet research. 2025 Apr 3;27:e59507-7. https://doi.org/10.2196/59507
47. S Oliveira J, Sherrington C, R Y Zheng E, Franco MR, Tiedemann A. Effect of interventions using physical activity trackers on physical activity in people aged 60 years and over: A systematic review and meta-analysis. British journal of Sports medicine. 2019 Aug 9;54(20):bjsports-2018-100324. https://doi.org/10.1136/bjsports-2018-100324
48. Zhang Z, Giordani B, Margulis A, Chen W. Efficacy and acceptability of using wearable activity trackers in older adults living in retirement communities: A mixed method study. BMC geriatrics. 2022 Mar 21;22(1). https://doi.org/10.1186/s12877-022-02931-w
49. Li Y, Li Q, Chen X. Effectiveness of exercise based on wearable electronic devices on lower limb strength and balance in older adults: A systematic review and meta-analysis. Frontiers in Public health. 2026 Feb 25;14. https://doi.org/10.3389/fpubh.2026.1778082
50. Ferrari L, Bochicchio G, Bottari A, Scarton A, Cavedon V, Milanese C, et al. Feasibility and effectiveness of a 6-month, home-based, resistance exercise delivered by a remote technological solution in healthy older adults. Archives of Gerontology and geriatrics. 2024 Jul 5;127:105559-9. https://doi.org/10.1016/j.archger.2024.105559
51. McGarrigle L, Boulton E, Todd C. Map the apps: A rapid review of digital approaches to support the engagement of older adults in strength and balance exercises. BMC geriatrics. 2020 Nov 18;20(1). https://doi.org/10.1186/s12877-020-01880-6
52. Soto-Bagaria L, Eis S, Laura Mónica Pérez, Villa-García L, Oriol de Solà-Morales, Carrion C, et al. Mobile applications to prescribe physical exercise in frail older adults: Review of the available tools in app stores. Age and ageing. 2023 Dec 1;52(12). https://doi.org/10.1093/ageing/afad227
53. Netz Y, Salit Bar-Shalom, Argov E, Arnon M, Eti Benmoha, Ziv Yekutieli, et al. A smartphone platform for remote motor fitness assessment and AI-generated personalized exercise programs for older adults: Randomized controlled trial. Journal of Medical internet research. 2025 Oct 15;27:e73145-5. https://doi.org/10.2196/73145
54. Coates W, Wahlström J. Lean: Real-time analysis of resistance training using wearable computing. Sensors. 2023 May 9;23(10):4602. https://doi.org/10.3390/s23104602
55. Bishop Dj, Beck B, Biddle Sjh, Denay Kl, Ferri A, Gibala Mj, et al. Physical activity and exercise intensity terminology: A joint american college of Sports medicine (ACSM) expert statement and exercise and sport science Australia (ESSA) consensus statement. Medicine & Science in Sports & Exercise. 2025 Nov;57(11):2599-613. https://doi.org/10.1249/mss.0000000000003795
56. Brennan TR, Weakley J, Johnston RD, Creaby MW. Exercise classification in resistance training: A systematic review of technological approaches. Sports medicine. 2025 Jul 31;. https://doi.org/10.1007/s40279-025-02281-8
57. Conger Sa, Guo J, Fulkerson Sm, Pedigo L, Chen H, Bassett Dr. Objective assessment of strength training exercises using a wrist-worn accelerometer. Medicine & Science in Sports & Exercise. 2016 Sep;48(9):1847-55. https://doi.org/10.1249/MSS.0000000000000949
58. Igor Pernek, Gregorij Kurillo, Gregor Stiglic, Ruzena Bajcsy. Recognizing the intensity of strength training exercises with wearable sensors. Journal of Biomedical Informatics. 2015 Oct 17;58:145-55. https://doi.org/10.1016/j.jbi.2015.09.020
59. Schorr EN, Gepner AD, Dolansky MA, Forman DE, Park LG, Petersen KS, et al. Harnessing mobile health technology for Secondary cardiovascular disease prevention in older adults: A scientific statement from the american heart association. Circulation: Cardiovascular quality and outcomes. 2021 Apr;14(5). https://doi.org/10.1161/hcq.0000000000000103
60. Bertolazzi A, Quaglia V, Bongelli R. Barriers and facilitators to health technology adoption by older adults with chronic diseases: An integrative systematic review. BMC public health. 2024 Feb 16;24(1):506. https://doi.org/10.1186/s12889-024-18036-5
61. Ahmad NA, Mat Ludin AF, Shahar S, Mohd Noah SA, Mohd Tohit N. Willingness, perceived barriers and motivators in adopting mobile applications for health-related interventions among older adults: A scoping review. BMJ open. 2022 Mar;12(3):e054561. https://doi.org/10.1136/bmjopen-2021-054561
62. Tacca C, Vazquez Galvez A, Thompson IM, Bincalar AD, Tremmel C, Gomer R, et al. How well do older adult fitness technologies match user needs and preferences? Scoping review of 2014-2024 literature. Journal of Medical internet research. 2025 Sep 24;27:e75667. https://doi.org/10.2196/75667
63. Kastelic K, Dobnik M, Löfler S, Hofer C, Nejc Šarabon. Validity, reliability and sensitivity to change of three consumer-grade activity trackers in controlled and free-living conditions among older adults. Sensors. 2021 Sep 17;21(18):6245-5. https://doi.org/10.3390/s21186245
64. Beauchamp M, Kirkwood R, Cooper C, Brown M, K. Bruce Newbold, Scott D. Monitoring mobility in older adults using a global positioning system (GPS) smartwatch and accelerometer: A validation study. PLOS one. 2023 Dec 21;18(12):e0296159-9. https://doi.org/10.1371/journal.pone.0296159

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