The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Advances in wearable technology and applications in physical medicine and rehabilitation
Open accessAbstract
The development of miniature sensors that can be unobtrusively attached to the body or can be part of clothing items, such as sensing elements embedded in the fabric of garments, have opened countless possibilities of monitoring patients in the field over extended periods of time. This is of particular relevance to the practice of physical medicine and rehabilitation. Wearable technology addresses a major question in the management of patients undergoing rehabilitation, i.e. have clinical interventions a significant impact on the real life of patients? Wearable technology allows clinicians to gather data where it matters the most to answer this question, i.e. the home and community settings. Direct observations concerning the impact of clinical interventions on mobility, level of independence, and quality of life can be performed by means of wearable systems. Researchers have focused on three main areas of work to develop tools of clinical interest: 1)the design and implementation of sensors that are minimally obtrusive and reliably record movement or physiological signals, 2)the development of systems that unobtrusively gather data from multiple wearable sensors and deliver this information to clinicians in the way that is most appropriate for each application, and 3)the design and implementation of algorithms to extract clinically relevant information from data recorded using wearable technology. Journal of NeuroEngineering and Rehabilitation has devoted a series of articles to this topic with the objective of offering a description of the state of the art in this research field and pointing to emerging applications that are relevant to the clinical practice in physical medicine and rehabilitation.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Finally, applications in rehabilitation of remote monitoring systems relying on wearable sensors [36] have largely relied upon inertial sensors for movement detection and tracking.”
From A review of wearable sensors and systems with application in rehabilitation (2012) · cites this paper as [36]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Enhancing the quality of life through wearable technology
Park, S., & Jayaraman, S. (2003) · IEEE Engineering in Medicine and Biology Magazine · doi:10.1109/memb.2003.1213625 · Cited by 615
Physical rehabilitation outcome measures : a guide to enhanced clinical decision making
Finch, E. (2002) · Lippincott Williams & Wilkins eBooks · Cited by 399
Aminian, K., Robert, P. A., Buchser, E., Rutschmann, B., Hayoz, D., & Depairon, M. (1999) · Medical & Biological Engineering & Computing · doi:10.1007/bf02513304 · Cited by 309
User‐adaptive control of a magnetorheological prosthetic knee
Herr, H., & Wilkenfeld, A. (2003) · Industrial Robot the international journal of robotics research and application · doi:10.1108/01439910310457706 · Cited by 294
Motion pattern and posture: Correctly assessed by calibrated accelerometers
Foerster, F., & Fahrenberg, J. (2000) · Behavior Research Methods, Instruments, & Computers · doi:10.3758/bf03200815 · Cited by 188
Detecting absolute human knee angle and angular velocity using accelerometers and rate gyroscopes
Williamson, R., & Andrews, B. J. (2001) · Medical & Biological Engineering & Computing · doi:10.1007/bf02345283 · Cited by 185
Quantification of physical activities by means of ambulatory accelerometry: A validation study
Bussmann, J. B. J., Tulen, J. H. M., van Herel, E. C. G., & Stam, H. J. (1998) · Psychophysiology · doi:10.1017/s0048577298971153 · Cited by 142
Kay, T., & Huijbregts, M. P. J. (2003) · Physiotherapy Canada · doi:10.2310/6640.2003.35271 · Cited by 139
Automatic assessment of levodopa‐induced dyskinesias in daily life by neural networks
Keijsers, N., Horstink, M. W. I. M., & Gielen, S. C. A. M. (2002) · Movement Disorders · doi:10.1002/mds.10310 · Cited by 139
Is it feasible to reconstruct body segment 3-D position and orientation using accelerometric data?
Giansanti, D., Macellari, V., Maccioni, G., & Cappozzo, A. (2003) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2003.809490 · Cited by 127
Cited by
Sorted by citations
Items 301–385 of 385
Hybrid Integration Technology for Wearable Sensor Systems
Xie, L., Zheng, L., & Yang, G. (2016) · Advances in medical technologies and clinical practice book series · doi:10.4018/978-1-5225-1820-4.ch004 · Cited by 2
ANALYZING WAREHOUSE ERGONOMICS USING SMART TEXTILES
Mocan, A., Daniel, Ș. C., & Drăghici, A. (2017) · CBU International Conference Proceedings · doi:10.12955/cbup.v5.1092 · Cited by 2
Warm Robot Classroom_Using Wearable Technology as a Gateway to Culturally Responsive Teaching
Chen, A. C.-Y., & Lin, Y.-C. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-91152-6_19 · Cited by 2
Kordatos, G., & Stavrakis, M. (2018) · EAI International Conference on Smart Objects and Technologies for Social Good (GOODTECHS) · doi:10.1145/3284869.3284873 · Cited by 2
Gresham, B., Torres, J., Britton, J., Ma, Z., Parada, A., Gutierrez, M. L., Lawrence, M., & Tang, W. (2022) · IEEE Biomedical Circuits and Systems Conference (BioCAS) · doi:10.1109/biocas54905.2022.9948596 · Cited by 2
Altering Perceptions, Visualizing Sub-ground Metal Objects
Pedersen, A. (2020) · Emerging Science Journal · doi:10.28991/esj-2020-01224 · Cited by 2
Sensing Technologies for Biomedical Telemetry
Tamura, T. (2014) · Wiley eBooks · doi:10.1002/9781118893715.ch4 · Cited by 2
Wearable sensor technologies applied for post-stroke rehabilitation
Zhang, Z. (2015) · RMIT Research Repository (RMIT University Library) · doi:10.25439/rmt.27581808 · Cited by 2
Designing smart garments for rehabilitation
Wang, Q. (2018) · TU/e Research Portal · Cited by 2
Configurable Medical Cyber-Physical System Framework for Physical Activity Monitoring
Arafsha, F. (2019) · uO Research (University of Ottawa) · doi:10.20381/ruor-23045 · Cited by 2
Static Balance Characterization using a single IMU Located in the Lower Back: Preliminary Results
Pinto, D., Pastene, F., Godoy, J., Gómez, B., Ortega-Bastidas, P., & Aqueveque, P. (2022) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc48229.2022.9870929 · Cited by 1
Wearable Technology Safety and Ethics: A Systematic Review and Reappraisal
Holden, B., & Duffy, V. G. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-48057-7_24 · Cited by 1
Sudarso, S. P., Lin, Y. H., Kumada, J., Chu, M.-M., Bagci, F. S., & Kim, K. A. (2025) · IEEE Industry Applications Society Annual Meeting (IAS) · doi:10.1109/ias62731.2025.11061578 · Cited by 1
A Markovian Model for Harvested Power from Human Motion
Zhang, S., & Seyedi, A. (2013) · International Conference on Body Area Networks · doi:10.4108/icst.bodynets.2013.253912 · Cited by 1
A computational framework for wearable accelerometer-based activity and gesture recognition
Panchanathan, S., & Krishnan, N. C. (2010) · Cited by 1
Maleki, M., Faqihsolimani, M., & Mortezazadeh, B. (2015) · Annals of Applied Sport Science · doi:10.18869/acadpub.aassjournal.3.4.59 · Cited by 1
A Virtual System for Balance Control Assessment at Home
Spezialetti, M., Iacoviello, D., Petracca, A., & Placidi, G. (2017) · Communications in computer and information science · doi:10.1007/978-3-319-69694-2_2 · Cited by 1
Sensorized Garments Developed for Remote Postural and Motor Rehabilitation
Saggio, G., Sabato, V., & Mugavero, R. (2013) · IGI Global eBooks · doi:10.4018/978-1-4666-2979-0.ch018 · Cited by 1
Towards a Pattern Language Approach to Sharing Experiences in Healthcare Technology Evaluations
Doyle, J., Quigley, A. J., Nixon, P., & Caulfield, B. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-16607-5_8 · Cited by 1
Electrogoniometer error compensation, for hand position measurement during planar reaching movements
Naghibi, S. S., Maleki, A., Fallah, A., Ghassemi, F., & Zargaripour, E. (2023) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2023.104795 · Cited by 1
IoT-Based Multi-Level Sensors Electromyography (EMG) Acquisition System
Bacho, M. S. H., Saad, I., Ahmedy, F. B., Jeffree, M. S., Bolong, N., Lim, K. G., & Teo, K. T. K. (2023) · IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET) · doi:10.1109/iicaiet59451.2023.10291756 · Cited by 1
A Multi-Sensor Approach for Multi-Joint Tracking
Andò, B., Graziani, S., Manenti, M., & Greco, D. (2024) · IEEE International Instrumentation and Measurement Technology Conference · doi:10.1109/i2mtc60896.2024.10560934 · Cited by 1
Wearable Technologies in Rehabilitation
Mustafaoğlu, R. (2024) · doi:10.69860/nobel.9786053359418.17 · Cited by 1
Donati, D., Nasuti, M., Marcovigi, A., Costantini, R. C., Tedeschi, R., Ricci, V., MANTOVANI, M., Farì, G., Benedetti, M. G., Tarallo, L., et al. (2025) · Minerva Orthopedics · doi:10.23736/s2784-8469.25.04495-5 · Cited by 1
Design of Wireless Health Platforms
Au, L. K., Jordan, B. L., Wu, W. H., Batalin, M. A., & Kaiser, W. J. (2010) · Springer eBooks · doi:10.1007/978-1-4419-7384-9_4 · Cited by 1
Wearable U-HRM device for rural applications
Imran, M., & Qadeer, M. A. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-815370-3.00001-3 · Cited by 1
DWT Based Image Compression for Health Systems
Sawaneh, I. A. (2018) · Journal of Advance Research in Medical & Health Science · doi:10.53555/nnmhs.v4i9.603 · Cited by 1
Wearable Technologies in Academic Information Search
Gibson, R. M. (2018) · IGI Global eBooks · doi:10.4018/978-1-5225-5484-4.ch029 · Cited by 1
Advancing clinical gait analysis through technology and policy
Tan, J. (2009) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 1
Sistema de e-terapia inteligente. Un nuevo paradigma de psicoterapia asistida por ordenador
Álvarez, I. Z. (2012) · doi:10.4995/thesis/10251/16801 · Cited by 1
WAPA: A Wearable Framework for Aerobatic Pilot Aid
Righetti, X., Cardin, S., & Thalmann, D. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-10470-1_13 · Cited by 1
Quantitative motor assessment in patients with mobility limiting conditions using wearable sensors
Patel, S. (2012) · doi:10.17760/d20002546 · Cited by 2
A Mobile Application for Dual-task Gait Assessment of Cognitive Status
Blumenthal, J. (2017) · TSpace (University of Toronto) · Cited by 1
Western, M. J. (2016) · The University of Bath Online Publications Store (The University of Bath) · Cited by 1
Reactive Balance Control after Stroke: Towards Enhanced Clinical Understanding and Assessment
Inness, E. L. (2015) · TSpace (University of Toronto) · Cited by 1
Knowledge Extraction From Medical Imaging for Advanced Patient-Specific Musculoskeletal Models
Tho, M. H. B., & Dao, T. T. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-801238-3.99935-5 · Cited by 1
Characterisation and biomedical application of fabric sensors
Mestrovic, M. A. (2012) · RMIT Research Repository (RMIT University Library) · doi:10.25439/rmt.27351072
An Architecture for the Emotion-Based Ubiquitous Services in Wearable Computing Environment
Lee, H., & Kwon, J. (2010) · Communications in computer and information science · doi:10.1007/978-3-642-16444-6_23
Timmermans, A. A. A., Seelen, H. A. M., Willmann, R. D., & Kingma, H. (2007) · Data Archiving and Networked Services (DANS)
Patel, S., Hughes, R. L., Hester, T., Stein, J. M., Akay, M., Dy, J., & Bonato, P. (2010)
Self-citation12 Ondersteuning van mobiliteitsbehoud bij ouderen met bewegingstechnologie
Zijlstra, A., & Zijlstra, W. (2010) · Bohn Stafleu van Loghum eBooks · doi:10.1007/978-90-313-9327-5_12
Goodvin, C. (2007) · UVic’s Research and Learning Repository (University of Victoria)
Concurrent Validity of the Biostage for Assessment of Lower Extremity Joint Angles
Liu, J., Konz, S. M., Cheung, F. H., Szwilski, T. B., & Chapman, J. (2015) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931215591207
HEMS: a Hurricane Evacuation Management System.
Ambrose, A., Cardei, M., & Cardei, I. (2012)
Cochrane, K. A. (2016) · Summit (Simon Fraser University)
Smart Clothing for Health Care
García, N. M., Sousa, P. S., Trindade, I. G., Miguel, R. A. L., & Lucas, J. (2012) · Advances in healthcare information systems and administration book series · doi:10.4018/978-1-4666-0888-7.ch003
Wearable Technologies in Academic Information Search
Gibson, R. M. (2016) · Advances in educational technologies and instructional design book series · doi:10.4018/978-1-5225-0069-8.ch007 · Cited by 1
Wearable Technology: Improving Exercise Habits and Experiences in Adults
Rause, S. A. (2016)
Smart Soles: Posture Analysis Using Wireless Sensors
Flanagan, P. (2010)
Usability of a Photoplethysmography Device for a Biomedical Garment
Mečņika, V., Krieviņš, I., Kviesis-Kipge, E., Erts, R., & Marcinkevičs, Z. (2010) · International Conference on Biomedical Engineering
Design of an e-Textile sleeve for tracking knee rehabilitation for older adults
Byrne, C. (2013) · SMARTech Repository (Georgia Institute of Technology)
Emami-Abarghouei, B. (2016) · Memorial University Research Repository (Memorial University)
A Novel Joint Angle Measurement System to Monitor Hip Movement in Children with Hip Diseases
Leo, D. G., Abdullah, B. M., Perry, D. C., & Jones, H. (2019) · Advances in intelligent systems and computing · doi:10.1007/978-3-030-20476-1_2
Future perspectives on balance disorders in PD
Mancini, M., Nutt, J. G., & Horak, F. B. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-813874-8.00010-6
Cao, M. (2019) · University of Minnesota Digital Conservancy (University of Minnesota)
Sakthi, A. S., Mithra, B., Rakshana, M., Niveda, S., & Gayathri, K. (2021) · Lecture notes in networks and systems · doi:10.1007/978-981-16-2422-3_46
Trauth, E., & Browning, E. R. (2021) · IGI Global eBooks · doi:10.4018/978-1-6684-2414-8.ch031
Hybrid Integration Technology for Wearable Sensor Systems
Xie, L., Zheng, L., & Yang, G. (2017) · IGI Global eBooks · doi:10.4018/978-1-5225-3158-6.ch028
Bradley, D., & Russell, D. W. (2010) · Springer eBooks · doi:10.1007/978-1-84996-080-9_1
Hybrid Integration Technology for Wearable Sensor Systems
Xie, L., Zheng, L., & Yang, G. (2018) · IGI Global eBooks · doi:10.4018/978-1-5225-5484-4.ch008
Sensorized Garments Developed for Remote Postural and Motor Rehabilitation
Saggio, G., Sabato, V., & Mugavero, R. (2014) · IGI Global eBooks · doi:10.4018/978-1-4666-6339-8.ch026
Design and development of embedded/SQL home based upper limb rehabilitation
Babu, M. V., Ramya, V., & Murugan, V. S. (2022) · International Journal of Healthcare Management · doi:10.1080/20479700.2022.2124492
Asymmetric Constrained Control of a Cervical Orthotic Device Based on Barrier Sliding Modes
Mireles, C., Lozano, A., Ballesteros, M., Ortiz, D. C., & Salgado, I. (2022) · Applied Sciences · doi:10.3390/app122010286
Analysis on Smart Healthcare Monitoring Based on Compound Dimension
Vennilapriya, B., & Thangammal, C. B. (2024) · EAI Endorsed Transactions on Pervasive Health and Technology · doi:10.4108/eetpht.10.5266
Tatoglu, A., Pelczarski, B., Balaji, D., Campana, C. T., Asaki, T., & Altuger-Genc, G. (2024) · World Scientific Annual Review of Biomechanics · doi:10.1142/s2810958924300038
Wearable Pain Detector Using Heart Rate and Skin Conductance
Maulana, F. A., Torrie, B. D., Anugrah, P. H. G., Priharti, W., & Susanti, H. (2024) · IEEE International Conference on Computing (ICOCO) · doi:10.1109/icoco62848.2024.10928204
MNEs, Climate Change, and Heart Diseases: AI for Global Health Equity
Lane, H., Oakley, C. J., Hossain, T., Goswami, A., Sah, R. K., & Mishra, M. (2025) · CSR, sustainability, ethics & governance · doi:10.1007/978-3-031-80797-8_4
Wearable Technology and Sensor Data in Assistive Systems
Mukund, A. V. V. (2025) · IGI Global eBooks · doi:10.4018/979-8-3373-0194-5.ch010 · Cited by 1
Sharma, H., Mittal, P., Gurdev, & Mittal, V. (2025) · Wiley eBooks · doi:10.1002/9781394302895.ch16
Technological Advancements in the Detection and Quantification of Parkinsonian Tremor
Abola, P., & Lefebvre, K. M. (2025) · Topics in Geriatric Rehabilitation · doi:10.1097/tgr.0000000000000475
HEALTHME: Electronic Medical Assistant
Hernández-Chan, G., Villanueva-Escalante, M., & Villanueva-Escalante, M. (2024) · International Conference on Software Process Improvement (CIMPS) · doi:10.1109/cimps65195.2024.11095933
ColorX: A Fitness Tracker-Based Device for Rapid, Optical Sensing of Water Quality Parameters
Yallapragada, V. V. B., Ananthachar, A., Gowda, U., Chlochasaigh, F. N., O’Faoláin, L., & Devarapu, G. C. R. (2025) · Sensors · doi:10.3390/s25164935
Ha, S., Lee, J., No, J., Hwang, S., & Kim, W. (2025) · International Conference on Control, Automation and Systems (ICCAS) · doi:10.23919/iccas66577.2025.11301309
Misgar, M. M., & Bhatia, M. P. S. (2026) · Soft Computing · doi:10.1007/s00500-024-09832-7
Low, L. (2025) · IEEE MIT Undergraduate Research Technology Conference (URTC) · doi:10.1109/urtc68753.2025.11533010
Wearable neural biosensors for early detection of neurodegenerative diseases
Ahmad, I., Ravindra, K., Bhargavi, Y. B., Nagaraju, K. L., Mandava, J., Mim, T. J., & Dongare, S. A. (2026) · Discover Neuroscience · doi:10.1186/s13064-026-00302-4
Miró, A., Fernández‐García, R., Carrasco‐Marginet, M., García, F., & Irurtia, A. (2026) · Textile Research Journal · doi:10.1177/00405175261472739
Flexible Ultrathin Resistive Temperature Sensors for Glove-Based Assistive Technology
Alassaf, M., & Hassani, F. A. (2024) · doi:10.1109/bnm62684.2024.11643669
Metadata
- Authors
- Bonato, P.
- Affiliations
- Harvard University (US)
- Corresponding author
- Bonato, Paolo
- ORCID
- Bonato, Paolo
- Venue
- Journal of NeuroEngineering and Rehabilitation
- Published
- 2005-02-25
- Volume
- 2
- Issue
- 1
- Pages
- 2-2
- ISSN
- 1743-0003 (ISSN-L)
- PMC
- PMC552335
- OpenAlex
- W2095736475
- Cited by
- 385
- References
- 25
- Citations by year
- 2026: 4 · 2025: 18 · 2024: 22 · 2023: 18 · 2022: 20 · 2021: 14 · 2020: 16 · 2019: 17 · 2018: 31 · 2017: 22 · 2016: 23 · 2015: 22 · 2014: 22 · 2013: 20 · 2012: 21
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of NeuroEngineering and Rehabilitation (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
- Keywords
- wearable sensors, rehabilitation medicine, remote patient monitoring, mobility assessment, physiological signal recording, sensor fusion, quality of life
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
