The Use of Wearable Sensors to Monitor Patients' Progress During Rehabilitation
DOI:
https://doi.org/10.61919/jhrr.v3i1.24Keywords:
Wearable Sensors, Rehabilitation, Patient Monitoring, Physical Activity, Healthcare TechnologyAbstract
BACKGROUND: Wearable sensor technology provides a promising approach for objective monitoring of patients during rehabilitation, enabling personalized care and potentially improving rehabilitation outcomes.
OBJECTIVE: The aim of this study was to investigate the effectiveness of wearable sensors in tracking the progress of patients undergoing different types of rehabilitation.
METHODS: This prospective, observational study involved 120 patients in post-operative orthopedic, neurological, cardiac, and pulmonary rehabilitation. Patients were provided with wearable sensors to monitor daily step count and other related metrics, with data transmitted to a secure server for real-time analysis. Pre- and post-rehabilitation measures were compared for each patient to assess the effectiveness of the rehabilitation program.
RESULTS: All patient groups demonstrated a significant increase in the average daily step count from pre- to post-rehabilitation (p < 0.001). These results corroborated with clinical assessments of functional status, suggesting that wearable sensors provide an accurate reflection of patient progress during rehabilitation.
CONCLUSION: The findings support the integration of wearable sensor technology into rehabilitation programs, which could potentially facilitate personalized, efficient care, and improve patient outcomes.
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Del Din S, Godfrey A, Galna B, Lord S, Rochester L. Free-living gait characteristics in ageing and Parkinson’s disease: impact of environment and ambulatory bout length. Journal of neuroengineering and rehabilitation. 2016;13:1-12.
Chen H, Xue M, Mei Z, Bambang Oetomo S, Chen W. A review of wearable sensor systems for monitoring body movements of neonates. Sensors. 2016;16(12):2134.
Argent R, Slevin P, Bevilacqua A, Neligan M, Daly A, Caulfield B. Wearable sensor-based exercise biofeedback for orthopaedic rehabilitation: a mixed methods user evaluation of a prototype system. Sensors. 2019;19(2):432.
Shany T, Wang K, Liu Y, Lovell NH, Redmond SJ. Are we stumbling in our quest to find the best predictor? Over‐optimism in sensor‐based models for predicting falls in older adults. Healthcare technology letters. 2015;2(4):79-88.
Porciuncula F, Roto AV, Kumar D, Davis I, Roy S, Walsh CJ, et al. Wearable movement sensors for rehabilitation: a focused review of technological and clinical advances. Pm&r. 2018;10(9):S220-S32.
Capela NA, Lemaire ED, Baddour N. Novel algorithm for a smartphone-based 6-minute walk test application: algorithm, application development, and evaluation. Journal of neuroengineering and rehabilitation. 2015;12:1-13.
De Fazio R, Mastronardi VM, De Vittorio M, Visconti P. Wearable Sensors and Smart Devices to Monitor Rehabilitation Parameters and Sports Performance: An Overview. Sensors. 2023;23(4):1856.
Jalloul N. Wearable sensors for the monitoring of movement disorders. Biomedical journal. 2018;41(4):249-53.
Shull PB, Jirattigalachote W, Hunt MA, Cutkosky MR, Delp SL. Quantified self and human movement: a review on the clinical impact of wearable sensing and feedback for gait analysis and intervention. Gait & posture. 2014;40(1):11-9.
Kristoffersson A, Lindén M. A systematic review of wearable sensors for monitoring physical activity. Sensors. 2022;22(2):573.
Godfrey A, Hetherington V, Shum H, Bonato P, Lovell N, Stuart S. From A to Z: Wearable technology explained. Maturitas. 2018;113:40-7.
Zhang M, Lange B, Chang C-Y, Sawchuk AA, Rizzo AA, editors. Beyond the standard clinical rating scales: fine-grained assessment of post-stroke motor functionality using wearable inertial sensors. 2012 Annual international conference of the IEEE engineering in medicine and biology society; 2012: IEEE.
Patel S, Park H, Bonato P, Chan L, Rodgers M. A review of wearable sensors and systems with application in rehabilitation. Journal of neuroengineering and rehabilitation. 2012;9(1):1-17.
Cooper D, Bhuskute N, Walsh G. Exploring the impact and acceptance of wearable sensor technology for pre-and postoperative rehabilitation in knee replacement patients: a UK-based pilot study. JBJS Open Access. 2022;7(2).
Candelieri A, Zhang W, Messina E, Archetti F, editors. Automated rehabilitation exercises assessment in wearable sensor data streams. 2018 IEEE International Conference on Big Data (Big Data); 2018: IEEE.
Yang C-C, Hsu Y-L. A review of accelerometry-based wearable motion detectors for physical activity monitoring. Sensors. 2010;10(8):7772-88.
Bonato P, editor Advances in wearable technology and its medical applications. 2010 annual international conference of the IEEE engineering in medicine and biology; 2010: IEEE.
Tong K, Granat MH. A practical gait analysis system using gyroscopes. Medical engineering & physics. 1999;21(2):87-94.
Prill R, Walter M, Królikowska A, Becker R. A systematic review of diagnostic accuracy and clinical applications of wearable movement sensors for knee joint rehabilitation. Sensors. 2021;21(24):8221.
Bahadori S, Immins T, Wainwright TW. A review of wearable motion tracking systems used in rehabilitation following hip and knee replacement. Journal of rehabilitation and assistive technologies engineering. 2018;5:2055668318771816.
Lymberis A. Research and development of smart wearable health applications: the challenge ahead. Stud Health Technol Inform. 2004;108:155-61.
Bolam SM, Batinica B, Yeung TC, Weaver S, Cantamessa A, Vanderboor TC, et al. Remote patient monitoring with wearable sensors following knee arthroplasty. Sensors. 2021;21(15):5143.
Russell TG. Physical rehabilitation using telemedicine. Journal of telemedicine and telecare. 2007;13(5):217-20.
Albán-Cadena AC, Villalba-Meneses F, Pila-Varela KO, Moreno-Calvo A, Villalba-Meneses CP, Almeida-Galárraga DA. Wearable sensors in the diagnosis and study of Parkinson’s disease symptoms: A systematic review. Journal of Medical Engineering & Technology. 2021;45(7):532-45.
Taborri J, Palermo E, Rossi S, Cappa P. Gait partitioning methods: A systematic review. Sensors. 2016;16(1):66.
Seshadri DR, Davies EV, Harlow ER, Hsu JJ, Knighton SC, Walker TA, et al. Wearable sensors for COVID-19: a call to action to harness our digital infrastructure for remote patient monitoring and virtual assessments. Frontiers in Digital Health. 2020:8.
Papi E, Murtagh GM, McGregor AH. Wearable technologies in osteoarthritis: a qualitative study of clinicians’ preferences. BMJ open. 2016;6(1):e009544.
Lmberis A, Dittmar A. Advanced wearable health systems and applications-research and development efforts in the European union. IEEE Engineering in Medicine and Biology Magazine. 2007;26(3):29-33.
De Cannière H, Corradi F, Smeets CJ, Schoutteten M, Varon C, Van Hoof C, et al. Wearable monitoring and interpretable machine learning can objectively track progression in patients during cardiac rehabilitation. Sensors. 2020;20(12):3601.
Rashid A, Hasan O. Wearable technologies for hand joints monitoring for rehabilitation: A survey. Microelectronics Journal. 2019;88:173-83.
Panwar M, Biswas D, Bajaj H, Jöbges M, Turk R, Maharatna K, et al. Rehab-net: Deep learning framework for arm movement classification using wearable sensors for stroke rehabilitation. IEEE Transactions on Biomedical Engineering. 2019;66(11):3026-37.
He Z, Liu T, Yi J. A wearable sensing and training system: Towards gait rehabilitation for elderly patients with knee osteoarthritis. IEEE Sensors Journal. 2019;19(14):5936-45.
Gurchiek RD, Choquette RH, Beynnon BD, Slauterbeck JR, Tourville TW, Toth MJ, et al., editors. Remote gait analysis using wearable sensors detects asymmetric gait patterns in patients recovering from ACL reconstruction. 2019 IEEE 16th International Conference on Wearable and Implantable Body Sensor Networks (BSN); 2019: IEEE.
Díaz S, Stephenson JB, Labrador MA. Use of wearable sensor technology in gait, balance, and range of motion analysis. Applied Sciences. 2019;10(1):234.
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Copyright (c) 2023 Dr Asad Aziz, Dr Nadia Saleem, Dr Zunaira Shafaqat
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