Evidence gap map: Use of wearable technology for health and care outcomes

Version 3, 18 August 2025

NIHR Bristol Evidence Synthesis Group

Contributors: Jennifer Palmer, Katie Webster, Gabriel Barreto, Francesca Spiga, Philippa Davies, Sarah Davies, Sarah Dawson, Deborah Caldwell, Julian Higgins

Background

Wearable devices are increasingly used by the general public and healthcare professionals with the aim of monitoring general health and facilitating earlier diagnosis. We aimed to assess the current availability of systematic review evidence on the use of wearable devices for early detection of primary disease (Use case 1), the promotion of behaviour changes to improve health (Use case 2), and pre- and post-operative care (Use case 3).

These were the aims set out in our original proposal:

Primary aim: to understand the synthesized evidence in relation to wearables according to each of three use cases:

  • Use case 1 (UC1): Earlier detection of (primary and secondary) conditions, with a focus on clinical effectiveness.
  • Use case 2 (UC2): Behaviour change for better health outcomes, and
  • Use case 3 (UC3): Pre-operative assessment and post-operative recovery.

Secondary aim: to indicate where there are evidence gaps, to enable the targeting of evidence-gathering to inform development of wearables policy.

Methods

We searched Ovid Medline and Ovid Embase for articles published from 1 January 2020 to 21 May 2025. We independently screened titles and abstracts from 2372 records for inclusion in duplicate, with conflicts resolved by team discussion. 321 full texts were each assessed for eligibility by one team member, with all excluded articles at this stage checked by a second team member and discussed if needed. Following this process, we included 183 systematic reviews: 52 reviews for Use case 1; 110 reviews for Use case 2, and 23 reviews for Use case 3.

Where the intervention of interest within the systematic review was wearables entirely, we extracted their search information and results, eligibility criteria, and the bottom-line results/conclusions from the review. Where the intervention of interest was a wider intervention that included wearables within, we extracted more limited information on the intervention type that included wearables eligible for the review, and health condition, health behaviour or type of surgery for use cases 1, 2 or 3 respectively.

All included reviews were included on the visual Evidence Gap Maps, produced using EPPI reviewer and the Evidence Gap Map software, EPPI Mapper.

Results

Use-case 1: Wearables for earlier detection or diagnosis of primary conditions

We identified 25 systematic reviews that matched our eligibility criteria for wearables for Use case 1, and 27 systematic reviews on wider interventions that included wearables. We identified systematic reviews investigating both clinical effectiveness (whether the wearable(s) lead(s) to a primary diagnosis earlier than had the wearable not been worn) and clinical accuracy (how accurate the wearable(s) is/are at leading to a diagnosis, which could be sensitivity, specificity or another suitable measure).

We included nine reviews for secondary detection of CVD outcomes within CVD populations. These are included in the UC1 map (filter by population “with current or previous CVD/mixed”) to see only these reviews.

For each map, refer to the ‘About’ tab at the top of the screen for more information. The ‘Filter’ options can be used to filter results by number of included studies in the review, population, or study designs included. Once the desired filter is selected, click on ‘view records’ to see the relevant systematic reviews. The key for colour-coding is at the bottom of the map.

The evidence gap map ‘UC1 – by effectiveness_accuracy’ shows type of wearable/intervention that includes wearables as rows and primary health condition detecting as columns, colour-coded by whether the review was investigating clinical effectiveness (pink) or clinical accuracy (purple).

The evidence gap map ‘UC1 – by population’ shows type of wearable/intervention that includes wearables as rows and primary health condition detecting as columns, colour-coded by whether the review was investigating a general/healthy population (pink), people suspected of having the health condition (blue), a mixed with/without a health condition population (purple), or population information not extracted/not reported (green).

Use case 2 – general population: Wearables for behaviour change for better health outcomes

We identified 43 systematic reviews matched our eligibility criteria for wearables for Use case 2, and 67 systematic reviews on wider interventions that included wearables.

The evidence gap map ‘UC2_by_population’ shows type of wearable/intervention that includes wearables as rows and health behaviour detecting as columns, colour-coded by whether the review was investigating a general/healthy population (green), with a health condition (pink, to add), or mixed population with/without a health condition (purple).

As there are a lot of systematic reviews included for Use case 2, particularly investigating the use of wearables on improving physical activity levels in those with health conditions, there is an additional filter for populations included in Use case 2. This may be useful to see reviews in those with a particular health condition, such as cancer, cardiovascular disease or mental health. Please refer to the ‘About’ tab at the top of the screen for more information and the ‘Filter’ tab to see all the filter options.

Use case 3 – Wearables for pre-operative assessment and post-operative recovery

We identified 11 systematic reviews that matched our eligibility criteria for wearables for Use case 3, and 12 systematic reviews on wider interventions that included wearables. We identified systematic reviews investigating both pre-operative assessment and post operative recovery.

The evidence gap map ‘UC3_by_pre-post’ shows type of wearable/intervention that includes wearables as rows and operation type as columns, colour-coded by whether the review was investigating pre-operative monitoring (green) or post-operative assessment (pink) (note, many reviews looked at both): UC3_by_pre-post.html / UC3_by_pre-post.zip

The evidence gap map ‘UC3_by_population’ shows type of wearable/intervention that includes wearables as rows and operation type as columns, colour-coded by whether the review was investigating an adult population (pink), older adult population (purple), or population information not extracted (green): UC3_by_population.html / UC3_by_population.zip

References to included systematic reviews

  1. Abd-Alrazaq A, AlSaad R, Harfouche M, Aziz S, Ahmed A, Damseh R, et al. Wearable Artificial Intelligence for Detecting Anxiety: Systematic Review and Meta-Analysis. J Med Internet Res. 2023;25:e48754.
  2. Abd-Alrazaq A, Aslam H, AlSaad R, Alsahli M, Ahmed A, Damseh R, et al. Detection of Sleep Apnea Using Wearable AI: Systematic Review and Meta-Analysis. J Med Internet Res. 2024;26:e58187.
  3. Abd-Alrazaq A, AlSaad R, Shuweihdi F, Ahmed A, Aziz S, Sheikh J. Systematic review and meta-analysis of performance of wearable artificial intelligence in detecting and predicting depression. npj digit. 2023;6(1):84.
  4. Belani S, Wahood W, Hardigan P, Placzek AN, Ely S. Accuracy of Detecting Atrial Fibrillation: A Systematic Review and Meta-Analysis of Wrist-Worn Wearable Technology. Cureus. 2021;13(12):e20362.
  5. Bogar B, Peto D, Sipos D, Furedi G, Keszthelyi A, Betlehem J, et al. Detection of Arrhythmias Using Smartwatches-A Systematic Literature Review. Healthcare (Basel). 2024;12(9):25.
  6. Elbey MA, Young D, Kanuri SH, Akella K, Murtaza G, Garg J, et al. Diagnostic Utility of Smartwatch Technology for Atrial Fibrillation Detection – A Systematic Analysis. J Atr Fibrillation. 2021;13(6):20200446.
  7. Khor YH, Khung SW, Ruehland WR, Jiao Y, Lew J, Munsif M, et al. Portable evaluation of obstructive sleep apnea in adults: A systematic review. Sleep Med Rev. 2023;68:101743.
  8. Lee MA, Song M, Bessette H, Roberts Davis M, Tyner TE, Reid A. Use of wearables for monitoring cardiometabolic health: A systematic review. International Journal of Medical Informatics. 2023;179:105218.
  9. Lopez Perales CR, Van Spall HGC, Maeda S, Jimenez A, Latcu DG, Milman A, et al. Mobile health applications for the detection of atrial fibrillation: a systematic review. Europace. 2021;23(1):11-28.
  10. Luo DY, Zhang ZW, Sibomana O, Izere S. Comparison of diagnostic accuracy of electrocardiogram-based versus photoplethysmography-based smartwatches for atrial fibrillation detection: A Systematic Review and Meta-Analysis. Ann Med Surg (Lond). 2025;87(4):2307-23.
  11. Mitratza M, Goodale BM, Shagadatova A, Kovacevic V, van de Wijgert J, Brakenhoff TB, et al. The performance of wearable sensors in the detection of SARS-CoV-2 infection: a systematic review. Lancet Digit Health. 2022;4(5):e370-e83.
  12. Moshawrab M, Adda M, Bouzouane A, Ibrahim H, Raad A. Smart Wearables for the Detection of Cardiovascular Diseases: A Systematic Literature Review. Sensors (Basel). 2023;23(2):11.
  13. Nazarian S, Lam K, Darzi A, Ashrafian H. Diagnostic Accuracy of Smartwatches for the Detection of Cardiac Arrhythmia: Systematic Review and Meta-analysis. J Med Internet Res. 2021;23(8):e28974.
  14. Pay L, Yumurtas AC, Satti DI, Hui JMH, Chan JSK, Mahalwar G, et al. Arrhythmias Beyond Atrial Fibrillation Detection Using Smartwatches: A Systematic Review. Anatol J Cardiol. 2023;27(3):126-31.
  15. Sanches CA, Silva GA, Librantz AFH, Sampaio LMM, Belan PA. Wearable Devices to Diagnose and Monitor the Progression of COVID-19 Through Heart Rate Variability Measurement: Systematic Review and Meta-Analysis. J Med Internet Res. 2023;25:e47112.
  16. Sastimoglu Z, Subramaniam S, Faisal AI, Jiang W, Ye A, Deen MJ. Wearable PPG Based BP Estimation Methods: A Systematic Review and Meta-Analysis. IEEE Journal of Biomedical & Health Informatics. 2025;29(4):2439-52.
  17. Shahid S, Iqbal M, Saeed H, Hira S, Batool A, Khalid S, et al. Diagnostic Accuracy of Apple Watch Electrocardiogram for Atrial Fibrillation: A Systematic Review and Meta-Analysis. JACC Adv. 2025;4(2):101538.
  18. Sibomana O, Hakayuwa CM, Obianke A, Gahire H, Munyantore J, Chilala MM. Diagnostic accuracy of ECG smart chest patches versus PPG smartwatches for atrial fibrillation detection: a systematic review and meta-analysis. BMC Cardiovascular Disorders. 2025;25(1):132.
  19. Singh B, Chastin S, Miatke A, Curtis R, Dumuid D, Brinsley J, et al. Real-World Accuracy of Wearable Activity Trackers for Detecting Medical Conditions: Systematic Review and Meta-Analysis. JMIR Mhealth Uhealth. 2024;12:e56972.
  20. Ballavenuto JMA, Tongtip N, Fischer NLS, Bardus M. Wearable devices, ischemic heart disease and cardiovascular outcomes: A systematic review and meta-analysis. Maturitas. 2025;193:108186.
  21. Ho JS, Ho ES, Yeo LL, Kong WK, Li TY, Tan BY, et al. Use of wearable technology in cardiac monitoring after cryptogenic stroke or embolic stroke of undetermined source: a systematic review. Singapore Med J. 2024;65(7):370-9.
  22. Kaihara T, Intan-Goey V, Scherrenberg M, Falter M, Frederix I, Dendale P. Impact of activity trackers on secondary prevention in patients with coronary artery disease: a systematic review and meta-analysis. Eur J Prev Cardiol. 2022;29(7):1047-56.
  23. Mohrag M, Mojiri ME, Hakami MS, Alghamdi MS, Moafa AY, Kreet SJ, et al. The Impact of Wearable Technologies on Blood Pressure Control in Hypertensive Patients: A Systematic Review and Meta-Analysis. Cureus. 2024;16(10):e71220.
  24. Özsezer G, Dağhan S. Effectiveness of wearable technologies used in the monitoring of cardiovascular diseases in the community: A systematic review of randomized controlled trials. Comput Biol Med. 2025;189(C):17.
  25. Singh J, Ellingson CJ, Gagarinova M, Thakkar R, Mehta N, Ahmad K, et al. Wearable Devices for Hemodynamic Assessment in Cardiovascular Disease: A Short Literature Review. Cardiol Rev. 2025.
  26. Adhibai R, Kosiyaporn H, Markchang K, Nasueb S, Waleewong O, Suphanchaimat R. Depressive symptom screening in elderly by passive sensing data of smartphones or smartwatches: A systematic review. PLoS ONE [Electronic Resource]. 2024;19(6):e0304845.
  27. Asadzadeh A, Kalankesh LR. A scope of mobile health solutions in COVID-19 pandemics. Inform Med Unlocked. 2021;23:100558.
  28. Babar F, Cheema AM, Ahmad Z, Sarfraz A, Sarfraz Z, Ashraff H, et al. Sensitivity and Specificity of Wearables for Atrial Fibrillation in Elderly Populations: A Systematic Review. Curr Cardiol Rep. 2023;25(7):761-79.
  29. Babatope EY, Ramirez-Acosta AA, Avila-Funes JA, Garcia-Vazquez M. The Potential of Automated Assessment of Cognitive Function Using Non-Neuroimaging Data: A Systematic Review. J Clin Med. 2024;13(23):22.
  30. Bazoukis G, Bollepalli SC, Chung CT, Li X, Tse G, Bartley BL, et al. Application of artificial intelligence in the diagnosis of sleep apnea. J Clin Sleep Med. 2023;19(7):1337-63.
  31. Cepukaityte G, Newton C, Chan D. Early detection of diseases causing dementia using digital navigation and gait measures: A systematic review of evidence. Alzheimer’s dement. 2024;20(4):3054-73.
  32. Chan A, Cai J, Qian L, Coutts B, Phan S, Gregson G, et al. In-Home Positioning for Remote Home Health Monitoring in Older Adults: Systematic Review. JMIR Aging. 2024;7:e57320.
  33. Cuevas-Chavez A, Hernandez Y, Ortiz-Hernandez J, Sanchez-Jimenez E, Ochoa-Ruiz G, Perez J, et al. A Systematic Review of Machine Learning and IoT Applied to the Prediction and Monitoring of Cardiovascular Diseases. Healthcare (Basel). 2023;11(16):09.
  34. Daniolou S, Rapp A, Haase C, Ruppert A, Wittwer M, Scoccia Pappagallo A, et al. Digital Predictors of Morbidity, Hospitalization, and Mortality Among Older Adults: A Systematic Review and Meta-Analysis. Front. 2020;2:602093.
  35. Duarte M, Pereira-Rodrigues P, Ferreira-Santos D. The Role of Novel Digital Clinical Tools in the Screening or Diagnosis of Obstructive Sleep Apnea: Systematic Review. J Med Internet Res. 2023;25:e47735.
  36. Hermans ANL, Gawalko M, Dohmen L, van der Velden RMJ, Betz K, Duncker D, et al. Mobile health solutions for atrial fibrillation detection and management: a systematic review. Clin. 2022;111(5):479-91.
  37. Hutton J, Lingawi S, Puyat JH, Kuo C, Shadgan B, Christenson J, et al. Sensor technologies to detect out-of-hospital cardiac arrest: A systematic review of diagnostic test performance. Resusc Plus. 2022;11:100277.
  38. Landry V, Matschek J, Pang R, Munipalle M, Tan K, Boruff J, et al. Audio-based digital biomarkers in diagnosing and managing respiratory diseases: a systematic review and bibliometric analysis. Eur. 2025;34(176).
  39. Lee S, Chu Y, Ryu J, Park YJ, Yang S, Koh SB. Artificial Intelligence for Detection of Cardiovascular-Related Diseases from Wearable Devices: A Systematic Review and Meta-Analysis. Yonsei Med J. 2022;63(Suppl):S93-S107.
  40. Loh HW, Ooi CP, Barua PD, Palmer EE, Molinari F, Acharya UR. Automated detection of ADHD: Current trends and future perspective. Computers in Biology and Medicine. 2022;146(no pagination).
  41. Manetas-Stavrakakis N, Sotiropoulou IM, Paraskevas T, Maneta Stavrakaki S, Bampatsias D, Xanthopoulos A, et al. Accuracy of Artificial Intelligence-Based Technologies for the Diagnosis of Atrial Fibrillation: A Systematic Review and Meta-Analysis. J Clin Med. 2023;12(20) (no pagination).
  42. Patel J, Hung C, Katapally TR. Evaluating predictive artificial intelligence approaches used in mobile health platforms to forecast mental health symptoms among youth: a systematic review. Psychiatry Res. 2025;343:116277.
  43. Prasitlumkum N, Cheungpasitporn W, Chokesuwattanaskul A, Thangjui S, Thongprayoon C, Bathini T, et al. Diagnostic accuracy of smart gadgets/wearable devices in detecting atrial fibrillation: A systematic review and meta-analysis. Arch Cardiovasc Dis. 2021;114(1):4-16.
  44. Saji AS, Komel A, Khan MH, Niraula S, Naeem B, Ahsan A, et al. Digital Health Technologies in Pediatric Infectious Disease and the Perspective of Patients and Healthcare Professionals: A Review. Health Science Reports. 2025;8(3) (no pagination).
  45. Shikha S, Sethia D, Indu S. A Systematic Review on Physiology-based Anxiety Detection using Machine Learning. Biomed. 2025;08:08.
  46. Tang EWL, Yip BHK, Yu CP, Wong SYS, Lee EKP. Sensitivity and specificity of automated blood pressure devices to detect atrial fibrillation: A systematic review and meta-analysis of diagnostic accuracy. Frontiers in Cardiovascular Medicine. 2022;9(no pagination).
  47. Teh SK, Rawtaer I, Tan HP. Predictive Accuracy of Digital Biomarker Technologies for Detection of Mild Cognitive Impairment and Pre-Frailty Amongst Older Adults: A Systematic Review and Meta-Analysis. IEEE Journal of Biomedical & Health Informatics. 2022;26(8):3638-48.
  48. Yamaguchi T, Mikami S, Maeda M, Saito T, Nakajima T, Yachida W, et al. Portable and wearable electromyographic devices for the assessment of sleep bruxism and awake bruxism: A literature review. Cranio. 2023;41(1):69-77.
  49. Zarate D, Stavropoulos V, Ball M, de Sena Collier G, Jacobson NC. Exploring the digital footprint of depression: a PRISMA systematic literature review of the empirical evidence. BMC Psychiatry. 2022;22(1):421.
  50. Jang JP, Lin HT, Chen YJ, Hsieh MH, Huang YC. Role of Remote Monitoring in Detection of Atrial Arrhythmia, Stroke Reduction, and Use of Anticoagulation Therapy　- A Systematic Review and Meta-Analysis. Circ J. 2020;84(11):1922-30.
  51. Sotirakos S, Fouda B, Mohamed Razif NA, Cribben N, Mulhall C, O’Byrne A, et al. Harnessing artificial intelligence in cardiac rehabilitation, a systematic review. Future Cardiol. 2022;18(2):154-64.
  52. Zobair KM, Houghton L, Tjondronegoro D, Sanzogni L, Islam MZ, Sarker T, et al. Systematic review of Internet of medical things for cardiovascular disease prevention among Australian first nations. Heliyon. 2023;9(11):e22420.
  53. Alam S, Zhang M, Harris K, Fletcher LM, Reneker JC. The Impact of Consumer Wearable Devices on Physical Activity and Adherence to Physical Activity in Patients with Cardiovascular Disease: A Systematic Review of Systematic Reviews and Meta-Analyses. Telemed J E Health. 2023;29(7):986-1000.
  54. Ashur C, Cascino TM, Lewis C, Townsend W, Sen A, Pekmezi D, et al. Do Wearable Activity Trackers Increase Physical Activity Among Cardiac Rehabilitation Participants? A SYSTEMATIC REVIEW AND META-ANALYSIS. J Mol Signal. 2021;41(4):249-56.
  55. Au WW, Recchia F, Fong DY, Wong SHS, Chan DKC, Capio CM, et al. Effect of wearable activity trackers on physical activity in children and adolescents: a systematic review and meta-analysis. Lancet Digit Health. 2024;6(9):e625-e39.
  56. Bahadori S, Hosseini M. Use of commercial WAMs for monitoring individual with lung cancer. A systematic review. Lung Cancer. 2024;198:108026.
  57. Blount DS, McDonough DJ, Gao Z. Effect of Wearable Technology-Based Physical Activity Interventions on Breast Cancer Survivors’ Physiological, Cognitive, and Emotional Outcomes: A Systematic Review. J Clin Med. 2021;10(9):08.
  58. Chan C, Sounderajah V, Normahani P, Acharya A, Markar SR, Darzi A, et al. Wearable Activity Monitors in Home Based Exercise Therapy for Patients with Intermittent Claudication: A Systematic Review. Eur J Vasc Endovasc Surg. 2021;61(4):676-87.
  59. Chen X, Wang F, Zhang H, Lin Y, Zhu S, Yang Y. Effectiveness of wearable activity trackers on physical activity among adolescents in school-based settings: a systematic review and meta-analysis. BMC Public Health. 2025;25(1):1050.
  60. Coughlin SS, Caplan LS, Stone R. Use of consumer wearable devices to promote physical activity among breast, prostate, and colorectal cancer survivors: a review of health intervention studies. J. 2020;14(3):386-92.
  61. Creaser AV, Clemes SA, Costa S, Hall J, Ridgers ND, Barber SE, et al. The Acceptability, Feasibility, and Effectiveness of Wearable Activity Trackers for Increasing Physical Activity in Children and Adolescents: A Systematic Review. International Journal of Environmental Research & Public Health [Electronic Resource]. 2021;18(12):08.
  62. Davey RJ, Zabatiero J, Beynon A, Wood G, Sy S, Rasmussen CL, et al. It is Feasible for 3 to 5-Year-Old Children to Use Smartwatch Activity Trackers: A Systematic Review. Acta Paediatr. 2025;16:16.
  63. de Oliveira VLP, de Paula TP, Viana LV. Pedometer- and accelerometer- based physical activity interventions in Type 2 diabetes: A systematic review and meta-analysis. Nutr Metab Cardiovasc Dis. 2024;34(3):548-58.
  64. Dehghan Ghahfarokhi A, Vosadi E, Barzegar H, Saatchian V. The Effect of Wearable and Smartphone Applications on Physical Activity, Quality of Life, and Cardiovascular Health Outcomes in Overweight/Obese Adults: A Systematic Review and Meta-analysis of Randomized Controlled Trials. Biological Research for Nursing. 2022;24(4):503-18.
  65. Eboreime KO, Hughes JG, Lee R, Luo J. Can Wearable Device Promote Physical Activity and Reduce Pain in People with Chronic Musculoskeletal Conditions? J Clin Med. 2025;14(3):05.
  66. Ferguson T, Olds T, Curtis R, Blake H, Crozier AJ, Dankiw K, et al. Effectiveness of wearable activity trackers to increase physical activity and improve health: a systematic review of systematic reviews and meta-analyses. Lancet Digit Health. 2022;4(8):e615-e26.
  67. Franssen WMA, Franssen G, Spaas J, Solmi F, Eijnde BO. Can consumer wearable activity tracker-based interventions improve physical activity and cardiometabolic health in patients with chronic diseases? A systematic review and meta-analysis of randomised controlled trials. Int. 2020;17(1):57.
  68. Freene N, Davey R, Sathiyakumar R, McPhail SM. Can physical activity measurement alone improve objectively-measured physical activity in primary care?: A systematic review and meta-analysis. Prev Med Rep. 2020;20:101230.
  69. Ha L, Mizrahi D, Wakefield CE, Cohn RJ, Simar D, Signorelli C. The Use of Activity Trackers in Interventions for Childhood Cancer Patients and Survivors: A Systematic Review. J Adolesc Young Adult Oncol. 2021;10(1):1-14.
  70. Han X, Li P, Yang Y, Liu X, Xia J, Wu W. An Exploration of the Application of Step Counter-Based Physical Activity Promotion Programs in Patients With Chronic Obstructive Pulmonary Disease: A Systematic Review. Front. 2021;9:691554.
  71. He Z, Zhao G, Li C, Xing Y, Xu A, Yang J, et al. Effects of using wearable devices on reducing sedentary time and prolonged sitting in healthy adults: a network meta-analysis. BMJ Open. 2024;14(11):e080186.
  72. Heizmann AN, Chapelle C, Laporte S, Roche F, Hupin D, Le Hello C. Impact of wearable device-based interventions with feedback for increasing daily walking activity and physical capacities in cardiovascular patients: a systematic review and meta-analysis of randomised controlled trials. BMJ Open. 2023;13(7):e069966.
  73. Hodkinson A, Kontopantelis E, Adeniji C, van Marwijk H, McMillian B, Bower P, et al. Interventions Using Wearable Physical Activity Trackers Among Adults With Cardiometabolic Conditions: A Systematic Review and Meta-analysis. JAMA Network Open. 2021;4(7):e2116382.
  74. Hodkinson A, Kontopantelis E, Zghebi SS, Grigoroglou C, McMillan B, Marwijk HV, et al. Association Between Patient Factors and the Effectiveness of Wearable Trackers at Increasing the Number of Steps per Day Among Adults With Cardiometabolic Conditions: Meta-analysis of Individual Patient Data From Randomized Controlled Trials. J Med Internet Res. 2022;24(8):e36337.
  75. Ibeneme SC, Mah J, Omeje C, Fortwengel G, Nwosu AO, Irem FO, et al. Effectiveness of pedometer-based walking programmes in improving some modifiable risk factors of stroke among community-dwelling older adults: a systematic review, theoretical synthesis and meta-analysis. BMC geriatr. 2024;24(1):516.
  76. Keats MR, Yu X, Sweeney Magee M, Forbes CC, Grandy SA, Sweeney E, et al. Use of Wearable Activity-Monitoring Technologies to Promote Physical Activity in Cancer Survivors: Challenges and Opportunities for Improved Cancer Care. International Journal of Environmental Research & Public Health [Electronic Resource]. 2023;20(6):08.
  77. Lai MYC, Mong MSA, Cheng LJ, Lau Y. The effect of wearable-delivered sleep interventions on sleep outcomes among adults: A systematic review and meta-analysis of randomized controlled trials. Nurs Health Sci. 2023;25(1):44-62.
  78. Larsen RT, Wagner V, Korfitsen CB, Keller C, Juhl CB, Langberg H, et al. Effectiveness of physical activity monitors in adults: systematic review and meta-analysis. BMJ. 2022;376:e068047.
  79. Li C, Chen X, Bi X. Wearable activity trackers for promoting physical activity: A systematic meta-analytic review. International Journal of Medical Informatics. 2021;152:104487.
  80. 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. J Med Internet Res. 2025;27:e59507.
  81. Liu JY, Kor PP, Chan CP, Kwan RY, Cheung DS. The effectiveness of a wearable activity tracker (WAT)-based intervention to improve physical activity levels in sedentary older adults: A systematic review and meta-analysis. Arch Gerontol Geriatr. 2020;91:104211.
  82. Longhini J, Marzaro C, Bargeri S, Palese A, Dell’Isola A, Turolla A, et al. Wearable Devices to Improve Physical Activity and Reduce Sedentary Behaviour: An Umbrella Review. Sports Med Open. 2024;10(1):9.
  83. Nuss K, Moore K, Nelson T, Li K. Effects of Motivational Interviewing and Wearable Fitness Trackers on Motivation and Physical Activity: A Systematic Review. Am J Health Promot. 2021;35(2):226-35.
  84. Pan M, Wu K, Zhao J, Hou X, Chen P, Wang B. Effects of wearable physical activity tracking for breast cancer survivors: A systematic review and meta-analysis. Int J Nurs Knowl. 2024;35(2):117-29.
  85. Patel HA, Hayden KA, Raffin Bouchal S, King-Shier K. Self-care Practices of Patients With Heart Failure Using Wearable Electronic Devices: A Systematic Review. Journal of Cardiovascular Nursing. 2022;20:20.
  86. Peng P, Zhang N, Huang J, Jiao X, Shen Y. Effectiveness of Wearable Activity Monitors on Metabolic Outcomes in Patients With Type 2 Diabetes: A Systematic Review and Meta-Analysis. Endocr Pract. 2023;29(5):368-78.
  87. Ringeval M, Wagner G, Denford J, Pare G, Kitsiou S. Fitbit-Based Interventions for Healthy Lifestyle Outcomes: Systematic Review and Meta-Analysis. J Med Internet Res. 2020;22(10):e23954.
  88. Shah AJ, Althobiani MA, Saigal A, Ogbonnaya CE, Hurst JR, Mandal S. Wearable technology interventions in patients with chronic obstructive pulmonary disease: a systematic review and meta-analysis. npj digit. 2023;6(1):222.
  89. Singh B, Zopf EM, Howden EJ. Effect and feasibility of wearable physical activity trackers and pedometers for increasing physical activity and improving health outcomes in cancer survivors: A systematic review and meta-analysis. J. 2022;11(2):184-93.
  90. Sousa AC, Ferrinho SN, Travassos B. The Use of Wearable Technologies in the Assessment of Physical Activity in Preschool- and School-Age Youth: Systematic Review. International Journal of Environmental Research & Public Health [Electronic Resource]. 2023;20(4):15.
  91. Szeto K, Arnold J, Singh B, Gower B, Simpson CEM, Maher C. Interventions Using Wearable Activity Trackers to Improve Patient Physical Activity and Other Outcomes in Adults Who Are Hospitalized: A Systematic Review and Meta-analysis. JAMA Network Open. 2023;6(6):e2318478.
  92. Tang MSS, Moore K, McGavigan A, Clark RA, Ganesan AN. Effectiveness of Wearable Trackers on Physical Activity in Healthy Adults: Systematic Review and Meta-Analysis of Randomized Controlled Trials. JMIR Mhealth Uhealth. 2020;8(7):e15576.
  93. Teo NR, Siew LED, Ang WHD, Lau Y. Wearable-Technology-Assisted Interventions for Breast-Cancer Survivors: A Meta-Analysis and Meta-Regression. Semin Oncol Nurs. 2023;39(3):151403.
  94. Wong SH, Tan ZYA, Cheng LJ, Lau ST. Wearable technology-delivered lifestyle intervention amongst adults with overweight and obese: A systematic review and meta-regression. International Journal of Nursing Studies. 2022;127:104163.
  95. Wu S, Li G, Du L, Chen S, Zhang X, He Q. The effectiveness of wearable activity trackers for increasing physical activity and reducing sedentary time in older adults: A systematic review and meta-analysis. Digit Health. 2023;9:20552076231176705.
  96. Agirre-Elordui S, Fernandez-Landa J, Olasagasti-Ibargoien J, Castaneda-Babarro A. Physical activity maintenance in colorectal cancer survivors after an exercise intervention applying behaviour change techniques: a systematic review and meta-analysis. J. 2024;05:05.
  97. Akinosun AS, Polson R, Diaz-Skeete Y, De Kock JH, Carragher L, Leslie S, et al. Digital Technology Interventions for Risk Factor Modification in Patients With Cardiovascular Disease: Systematic Review and Meta-analysis. JMIR Mhealth Uhealth. 2021;9(3):e21061.
  98. Al Swayied G, Guo H, Rookes T, Frost R, Hamilton FL. Assessing the Acceptability and Effectiveness of Mobile-Based Physical Activity Interventions for Midlife Women During Menopause: Systematic Review of the Literature. JMIR Mhealth Uhealth. 2022;10(12):e40271.
  99. Antoniou V, Davos CH, Kapreli E, Batalik L, Panagiotakos DB, Pepera G. Effectiveness of Home-Based Cardiac Rehabilitation, Using Wearable Sensors, as a Multicomponent, Cutting-Edge Intervention: A Systematic Review and Meta-Analysis. J Clin Med. 2022;11(13):29.
  100. Bahadori S, Collard S, Williams JM, Swain I. A review of current use of commercial wearable technology and smartphone apps with application in monitoring individuals following total hip replacement surgery. J Med Eng Technol. 2020;44(6):324-33.
  101. Belcher BR, Kang DW, Yunker AG, Dieli-Conwright CM. Interventions to Reduce Sedentary Behavior in Cancer Patients and Survivors: a Systematic Review. Curr Oncol Rep. 2022;24(11):1593-605.
  102. Butler S, Sculley D, Santos D, Fellas A, Girones X, Singh-Grewal D, et al. Effectiveness of eHealth and mHealth Interventions Supporting Children and Young People Living With Juvenile Idiopathic Arthritis: Systematic Review and Meta-analysis. J Med Internet Res. 2022;24(2):e30457.
  103. Casado-Robles C, Viciana J, Guijarro-Romero S, Mayorga-Vega D. Effects of Consumer-Wearable Activity Tracker-Based Programs on Objectively Measured Daily Physical Activity and Sedentary Behavior Among School-Aged Children: A Systematic Review and Meta-analysis. Sports Med Open. 2022;8(1):18.
  104. Chaudhry UAR, Wahlich C, Fortescue R, Cook DG, Knightly R, Harris T. The effects of step-count monitoring interventions on physical activity: systematic review and meta-analysis of community-based randomised controlled trials in adults. Int. 2020;17(1):129.
  105. Cheung AT, Li WHC, Ho LLK, Ho KY, Chan GCF, Chung JOK. Physical activity for pediatric cancer survivors: a systematic review of randomized controlled trials. J. 2021;15(6):876-89.
  106. Chua REC, Lau Y, Ang WW, Boey A, Lau ST. Effectiveness of wearable technology-based physical activity interventions for adults with type 2 diabetes mellitus: A systematic review and meta-regression. J Diabetes. 2024;16(10):e70002.
  107. Cora-Cruz MS, Wilson EM, Vargas GB, Thompson V, Enenmoh I, Goffe C, et al. Applications of Mobile Health Technologies to Address Cardiometabolic Health Disparities in the United States: A Systematic Review. Ethnicity & Disease. 2023;33(4):180-93.
  108. D’Amore C, Reid JC, Chan M, Fan S, Huang A, Louie J, et al. Interventions Including Smart Technology Compared With Face-to-face Physical Activity Interventions in Older Adults: Systematic Review and Meta-analysis. J Med Internet Res. 2022;24(10):e36134.
  109. Daryabeygi-Khotbehsara R, Shariful Islam SM, Dunstan D, McVicar J, Abdelrazek M, Maddison R. Smartphone-Based Interventions to Reduce Sedentary Behavior and Promote Physical Activity Using Integrated Dynamic Models: Systematic Review. J Med Internet Res. 2021;23(9):e26315.
  110. de Leeuwerk ME, Bor P, van der Ploeg HP, de Groot V, van der Schaaf M, van der Leeden M. The effectiveness of physical activity interventions using activity trackers during or after inpatient care: a systematic review and meta-analysis of randomized controlled trials. Int. 2022;19(1):59.
  111. Daniels K, Quadflieg K, Bonnechere B. Mobile health interventions for active aging: a systematic review and meta-analysis on the effectiveness of physical activity promotion. Mhealth. 2025;11:4.
  112. Delva S, Waligora Mendez KJ, Cajita M, Koirala B, Shan R, Wongvibulsin S, et al. Efficacy of Mobile Health for Self-management of Cardiometabolic Risk Factors: A Theory-Guided Systematic Review. Journal of Cardiovascular Nursing. 2021;36(1):34-55.
  113. Dorri S, Asadi F, Olfatbakhsh A, Kazemi A. A Systematic Review of Electronic Health (eHealth) interventions to improve physical activity in patients with breast cancer. Breast Cancer. 2020;27(1):25-46.
  114. Dwiputra B, Santoso A, Purwowiyoto BS, Radi B, Ambari AM, Desandri DR, et al. Smartphone-Based Cardiac Rehabilitation Program Improves Functional Capacity in Coronary Heart Disease Patients: A Systematic Review and Meta-Analysis. Glob Heart. 2023;18(1):42.
  115. Emberson MA, Lalande A, Wang D, McDonough DJ, Liu W, Gao Z. Effectiveness of Smartphone-Based Physical Activity Interventions on Individuals’ Health Outcomes: A Systematic Review. BioMed Research International. 2021;2021(no pagination).
  116. Ester M, Eisele M, Wurz A, McDonough MH, McNeely M, Culos-Reed SN. Current Evidence and Directions for Future Research in eHealth Physical Activity Interventions for Adults Affected by Cancer: Systematic Review. JMIR Cancer. 2021;7(3):e28852.
  117. Flaucher M, Zakreuskaya A, Nissen M, Mocker A, Fasching PA, Beckmann MW, et al. Evaluating the Effectiveness of Mobile Health in Breast Cancer Care: A Systematic Review. Oncologist. 2023;28(10):e847-e58.
  118. Freak-Poli R, Cumpston M, Albarqouni L, Clemes SA, Peeters A. Workplace pedometer interventions for increasing physical activity. Cochrane Database of Systematic Reviews. 2020;7:CD009209.
  119. Guerrero-Jimenez M, Ruiz M, Gutierrez-Rojas L, Jimenez-Munoz L, Baca-Garcia E, Porras-Segovia A. Use of new technologies for the promotion of physical activity in patients with mental illness: A systematic review. World j. 2023;13(4):182-90.
  120. Hoover RL, Xu J, Conklin JL, Nichols HB, Smitherman A, Valle CG, et al. Physical Activity Intervention Characteristics and Effects on Behavioral and Health-Related Outcomes Among Adolescents and Young Adults Living with and Beyond Cancer: A Systematic Review. J Adolesc Young Adult Oncol. 2024;13(1):55-79.
  121. Kamaruddin PSNM, Nawi AM, Manaf MRA, Yaman MN, Abd Malek AM. A Meta-Analysis of eHealth Interventions on Ischaemic Heart Disease Health Outcomes. Glob Heart. 2023;18(1) (no pagination).
  122. Khoo S, Mohbin N, Ansari P, Al-Kitani M, Muller AM. mHealth Interventions to Address Physical Activity and Sedentary Behavior in Cancer Survivors: A Systematic Review. International Journal of Environmental Research & Public Health [Electronic Resource]. 2021;18(11):28.
  123. Kim H, Kim G, Kim Y, Ha J. The Effects of ICT-Based Interventions on Physical Mobility of Older Adults: A Systematic Literature Review and Meta-Analysis. International Journal of Clinical Practice. 2023;2023(no pagination).
  124. Kwan RYC, Salihu D, Lee PH, Tse M, Cheung DSK, Roopsawang I, et al. The effect of e-health interventions promoting physical activity in older people: a systematic review and meta-analysis. Eur. 2020;17:7.
  125. Laranjo L, Ding D, Heleno B, Kocaballi B, Quiroz JC, Tong HL, et al. Do smartphone applications and activity trackers increase physical activity in adults? Systematic review, meta-analysis and metaregression. BJSM online. 2021;55(8):422-32.
  126. Li R, Wang M, Chen S, Zhang L. Comparative efficacy and adherence of telehealth cardiac rehabilitation interventions for patients with cardiovascular disease: A systematic review and network meta-analysis. International Journal of Nursing Studies. 2024;158:104845.
  127. Lynch C, Bird S, Lythgo N, Selva-Raj I. Changing the Physical Activity Behavior of Adults With Fitness Trackers: A Systematic Review and Meta-Analysis. Am J Health Promot. 2020;34(4):418-30.
  128. McLoughlin RF, Clark VL, Urroz PD, Gibson PG, McDonald VM. Increasing physical activity in severe asthma: a systematic review and meta-analysis. Eur Respir J. 2022;60(6):12.
  129. Metzendorf MI, Wieland LS, Richter B. Mobile health (m-health) smartphone interventions for adolescents and adults with overweight or obesity. Cochrane Database of Systematic Reviews. 2024;2:CD013591.
  130. Monninghoff A, Kramer JN, Hess AJ, Ismailova K, Teepe GW, Car LT, et al. Long-term effectiveness of mHealth physical activity interventions: Systematic review and meta-analysis of randomized controlled trials. J Med Internet Res. 2021;23(4) (no pagination).
  131. Nash EA, Critchley JA, Pearson F, Awad SF, Abu-Raddad LJ, Abu-Hijleh FM, et al. A systematic review of interventions to promote physical activity in six Gulf countries. PLoS ONE [Electronic Resource]. 2021;16(10):e0259058.
  132. Nieste I, Franssen WMA, Spaas J, Bruckers L, Savelberg HHCM, Eijnde BO. Lifestyle interventions to reduce sedentary behaviour in clinical populations: A systematic review and meta-analysis of different strategies and effects on cardiometabolic health. Preventive Medicine. 2021;148(no pagination).
  133. Oliveira JS, Sherrington C, E RYZ, 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. BJSM online. 2020;54(20):1188-94.
  134. Oliveira ACN, Guariente SMM, Zazula R, Mesas AE, Oliveira CEC, Reiche EMV, et al. Hybrid and Remote Psychosocial Interventions Focused on Weight and Sedentary Behavior Management Among Patients with Severe Mental Illnesses: a Systematic Review. Psychiatr Q. 2022;93(3):813-40.
  135. Page EJ, Massey AS, Prado-Romero PN, Albadawi S. The Use of Self-Monitoring and Technology to Increase Physical Activity: A Review of the Literature. Perspect Behav Sci. 2020;43(3):501-14.
  136. Peng S, Othman AT, Khairani AZ, Zeng G, Xiaogang Z, Fang Y. Effectiveness of pedometer- and accelerometer-based interventions in improving physical activity and health-related outcomes among college students: A systematic review and meta-analysis. Digit Health. 2023;9:20552076231188213.
  137. Pinto A, Piva SR, Rocha A, Gomes-Neto M, Atallah AN, Saconato H, et al. Digital technology for delivering and monitoring exercise programs for people with cystic fibrosis. Cochrane Database of Systematic Reviews. 2023;6:CD014605.
  138. Pradal-Cano L, Lozano-Ruiz C, Pereyra-Rodriguez JJ, Saigi-Rubio F, Bach-Faig A, Esquius L, et al. Using mobile applications to increase physical activity: A systematic review. International Journal of Environmental Research and Public Health. 2020;17(21):1-16.
  139. Pudkasam S, Feehan J, Talevski J, Vingrys K, Polman R, Chinlumprasert N, et al. Motivational strategies to improve adherence to physical activity in breast cancer survivors: A systematic review and meta-analysis. Maturitas. 2021;152:32-47.
  140. Reilly C, Sails J, Stavropoulos-Kalinoglou A, Birch RJ, McKenna J, Clifton IJ, et al. Physical activity promotion interventions in chronic airways disease: a systematic review and meta-analysis. Eur. 2023;32(167):31.
  141. Rodriguez-Gonzalez P, Hassan MA, Gao Z. Effects of Family-Based Interventions Using Mobile Apps on Youth’s Physical Activity: A Systematic Review. J Clin Med. 2022;11(16):17.
  142. Rowland S, Bach C, Simon K, Westmark DM, Sperling E. Effectiveness of digital health interventions to increase cardiorespiratory fitness: A systematic review and meta-analysis. Digit Health. 2024;10:20552076241282381.
  143. Sari YP, Herman H, Fajria L, Herien Y, Susanti E, Lin CY. The impact of m-health interventions on gestational weight gain and physical activity among pregnant women with overweight and obesity: A meta-analysis of randomized controlled trials. Midwifery. 2025;146:104399.
  144. Sediva H, Cartwright T, Robertson C, Deb SK. Behavior Change Techniques in Digital Health Interventions for Midlife Women: Systematic Review. JMIR Mhealth Uhealth. 2022;10(11):e37234.
  145. Sevic A, Hashemi NS, Thorrisen MM, Stromstad K, Skarpaas LS, Storm M, et al. Effectiveness of eHealth Interventions Targeting Employee Health Behaviors: Systematic Review. J Med Internet Res. 2023;25(no pagination).
  146. Shankaranarayana AM, Jagadish A, Nimmy J, Natarajan M, Janssen H, Solomon JM. Non-therapeutic strategies to promote physical activity of stroke survivors in hospital settings: A systematic review. Journal of Bodywork and Movement Therapies. 2023;36:192-202.
  147. Shaw G, Whelan ME, Armitage LC, Roberts N, Farmer AJ. Are COPD self-management mobile applications effective? A systematic review and meta-analysis. npj Primary Care Respiratory Medicine. 2020;30(1) (no pagination).
  148. Takemura N, Ho MH, Cheung DST, Lin CC. Effectiveness of motivational strategies on physical activity behavior and associated outcomes in patients with cancer: A systematic review and meta-analysis. Worldviews Evid Based Nurs. 2024;21(3):253-62.
  149. Tekaya AB, Hannech E, Dhia SB, Toulgui E, Bouden S, Rouached L, et al. Efficacy of Connected Devices in Promoting Physical Activity and Rehabilitation among Patients with Rheumatoid Arthritis and Spondyloarthritis: A Systematic Review. Rheumatology (Bulgaria). 2024;32(4):23-40.
  150. Thomas Craig KJ, Morgan LC, Chen CH, Michie S, Fusco N, Snowdon JL, et al. Systematic review of context-aware digital behavior change interventions to improve health. Translational Behavioral Medicine. 2021;11(5):1037-48.
  151. Tong HL, Alnasser A, Alshahrani NZ, Bawaked RA, AlAhmed R, Alsukait RF, et al. The Use of Mobile Technologies to Promote Physical Activity and Reduce Sedentary Behaviors in the Middle East and North Africa Region: Systematic Review and Meta-Analysis. J Med Internet Res. 2024;26:e53651.
  152. Virtanen M, Kerimaa H, Mannikko N, Mannisto M, Paalimaki-Paakki K, Lahtinen M, et al. Digital components and interaction types in counseling interventions for childhood and adolescent obesity: A systematic review. International Journal of Nursing Sciences. 2025;12(2):123-9.
  153. Wang E, Abrahamson K, Liu PJ, Ahmed A. Can Mobile Technology Improve Weight Loss in Overweight Adults? A Systematic Review. West J Nurs Res. 2020;42(9):747-59.
  154. Watson-Mackie K, Arundell L, Lander N, McKay FH, Jerebine A, Venetsanou F, et al. Technology-Supported Physical Activity and Its Potential as a Tool to Promote Young Women’s Physical Activity and Physical Literacy: Systematic Review. J Med Internet Res. 2024;26:e52302.
  155. Western MJ, Armstrong MEG, Islam I, Morgan K, Jones UF, Kelson MJ. The effectiveness of digital interventions for increasing physical activity in individuals of low socioeconomic status: a systematic review and meta-analysis. Int. 2021;18(1):148.
  156. Wu S, Li G, Shi B, Ge H, Chen S, Zhang X, et al. Comparative effectiveness of interventions on promoting physical activity in older adults: A systematic review and network meta-analysis. Digit Health. 2024;10:20552076241239182.
  157. Xiang XN, Wang ZZ, Hu J, Zhang JY, Li K, Chen QX, et al. Telehealth-Supported Exercise or Physical Activity Programs for Knee Osteoarthritis: Systematic Review and Meta-Analysis. J Med Internet Res. 2024;26:e54876.
  158. Xu L, Shi H, Shen M, Ni Y, Zhang X, Pang Y, et al. The Effects of mHealth-Based Gamification Interventions on Participation in Physical Activity: Systematic Review. JMIR Mhealth Uhealth. 2022;10(2):e27794.
  159. Xu H, Sui X, Zhang X, Pang Y, Yu T, Lian X, et al. Effectiveness of eHealth Interventions on Moderate-to-Vigorous Intensity Physical Activity Among Patients in Cardiac Rehabilitation: Systematic Review and Meta-analysis. J Med Internet Res. 2023;25(no pagination).
  160. Yoshihara R, Kitamura M, Ishihara K, Kanejima Y, Izawa KP. Mobile Health Intervention Reduces Sedentary Time and Physical Inactivity in Patients with Cardiovascular Diseases after Discharge: Systematic Review and Meta-Analysis. Heart and Mind. 2025;9(1):5-12.
  161. Zangger G, Bricca A, Liaghat B, Juhl CB, Mortensen SR, Andersen RM, et al. Benefits and Harms of Digital Health Interventions Promoting Physical Activity in People With Chronic Conditions: Systematic Review and Meta-Analysis. J Med Internet Res. 2023;25:e46439.
  162. Zhang M, Wang W, Li M, Sheng H, Zhai Y. Efficacy of Mobile Health Applications to Improve Physical Activity and Sedentary Behavior: A Systematic Review and Meta-Analysis for Physically Inactive Individuals. International Journal of Environmental Research and Public Health. 2022;19(8) (no pagination).
  163. Babaei N, Hannani N, Dabanloo NJ, Bahadori S. A Systematic Review of the Use of Commercial Wearable Activity Trackers for Monitoring Recovery in Individuals Undergoing Total Hip Replacement Surgery. Cyborg bionic syst. 2022;2022:9794641.
  164. Follis S, Chen Z, Mishra S, Howe CL, Toosizadeh N, Dohm M. Comparison of wearable sensor to traditional methods in functional outcome measures: A systematic review. J Orthop Res. 2021;39(10):2093-102.
  165. Gianzina E, Kalinterakis G, Delis S, Vlastos I, Platon Sachinis N, Yiannakopoulos CK. Evaluation of gait recovery after total knee arthroplasty using wearable inertial sensors: A systematic review. Knee. 2023;41:190-203.
  166. Iovanel G, Ayers D, Zheng H. The Role of Wearable Technology in Measuring and Supporting Patient Outcomes Following Total Joint Replacement: Review of the Literature. JMIR Perioper Med. 2023;6:e39396.
  167. Jin Z, Lee C, Zhang K, Jeong R, Gan TJ, Richman DC. Utilization of Wearable Pedometer Devices in the Perioperative Period: A Qualitative Systematic Review. Anesth Analg. 2023;136(4):646-54.
  168. King SW, Eltayeb M, van Duren BH, Jain S, Kerry J, Pandit HG, et al. Wearable Sensors to Guide Remote Rehabilitation Following Knee Arthroplasty Surgery. Indian j. 2023;57(5):624-34.
  169. Latif A, Al Janabi HF, Joshi M, Fusari G, Shepherd L, Darzi A, et al. Use of commercially available wearable devices for physical rehabilitation in healthcare: a systematic review. BMJ Open. 2024;14(11):e084086.
  170. Loo JH, Hai HH, Bin Abd Razak HR. Effectiveness of Sensor-based Rehabilitation in Improving Outcomes in Patients Undergoing Total Knee Arthroplasty. Surg Technol Int. 2022;41:301-14.
  171. Master H, Bley JA, Coronado RA, Robinette PE, White DK, Pennings JS, et al. Effects of physical activity interventions using wearables to improve objectively-measured and patient-reported outcomes in adults following orthopaedic surgical procedures: A systematic review. PLoS ONE [Electronic Resource]. 2022;17(2):e0263562.
  172. Memon A, Lec P, Lenis A, Sharma V, Wood E, Schade G, et al. Relationship Between Mobile Digital Sensor Monitoring and Perioperative Outcomes: Systematic Review. JMIR Perioper Med. 2021;4(1):e21571.
  173. Prill R, Walter M, Krolikowska A, Becker R. A Systematic Review of Diagnostic Accuracy and Clinical Applications of Wearable Movement Sensors for Knee Joint Rehabilitation. Sensors (Basel). 2021;21(24):09.
  174. Albino de Queiroz D, Andre da Costa C, Aparecida Isquierdo Fonseca de Queiroz E, Folchini da Silveira E, da Rosa Righi R. Internet of Things in active cancer Treatment: A systematic review. J Biomed Inform. 2021;118:103814.
  175. Chow A, Kaplan M, Damaraju K, Carmichael T, Jermyn R. The Use of Wearables and Smart Phone Apps for a Non-Inferior Recovery after Lower Limb Total Joint Arthroplasty: A Systematic Review and Meta-Analysis. Journal of Musculoskeletal Research. 2025;28(1) (no pagination).
  176. Constantinescu D, Pavlis W, Rizzo M, Vanden Berge D, Barnhill S, Hernandez VH. The role of commercially available smartphone apps and wearable devices in monitoring patients after total knee arthroplasty: a systematic review. EFORT Open Rev. 2022;7(7):481-90.
  177. Dawes J, Varghese C, Russell MM, Lin AY. Mobile health technology for remote home monitoring after surgery: a meta-analysis. British Journal of Surgery. 2021;108(11):1304-14.
  178. Escamilla-Nunez R, Michelini A, Andrysek J. Biofeedback Systems for Gait Rehabilitation of Individuals with Lower-Limb Amputation: A Systematic Review. Sensors (Basel). 2020;20(6):14.
  179. Gordon AM, Nian P, Baidya J, Scuderi GR, Mont MA. Randomized Controlled Studies on Smartphone Applications and Wearable Devices for Postoperative Rehabilitation after Total Knee Arthroplasty: A Systematic Review. J Arthroplasty. 2025;27:27.
  180. Haveman ME, Jonker LT, Hermens HJ, Tabak M, de Vries JP. Effectiveness of current perioperative telemonitoring on postoperative outcome in patients undergoing major abdominal surgery: A systematic review of controlled trials. J Telemed Telecare. 2024;30(2):215-29.
  181. Knight SR, Ng N, Tsanas A, McLean K, Pagliari C, Harrison EM. Mobile devices and wearable technology for measuring patient outcomes after surgery: a systematic review. npj digit. 2021;4(1):157.
  182. Lee S, Lim JJ, Kourounis G, Cheong J, Courtney M. Remote Patient Monitoring Following Same-Day Discharge Bariatric Surgery: A Systematic Review and Meta-analysis. Obesity Surgery. 2025;35(4):1357-76.
  183. Sodhi N, Hameed D, Barrack RL, Schneider AM, Bhave A, Mont MA. Use of Remote Physiologic and Therapeutic Monitoring Following Total Knee Arthroplasty. Surg Technol Int. 2023;42:321-8.