The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index.
Wearable Sensors and Systems
Open accessAbstract
It is now more than 50 years since the time when clinical monitoring of individuals in the home and community settings was first envisioned. Until recently, technologies to enable such vision were lacking. However, wearable sensors and systems developed over the past decade have provided the tools to finally implement and deploy technology with the capabilities required by researchers in the field of patients' home monitoring. As discussed, potential applications of these technologies include the early diagnosis of diseases such as congestive heart failure, the prevention of chronic conditions such as diabetes, improved clinical management of neurodegenerative conditions such as Parkinson's disease, and the ability to promptly respond to emergency situations such as seizures in patients with epilepsy and cardiac arrest in subjects undergoing cardiovascular monitoring. Current research efforts are now focused on the development of more complex systems for home monitoring of individuals with a variety of preclinical and clinical conditions. Recent research on the clinical assessment of wearable technology promises to deliver methodologies that are expected to lead to clinical adoption within the next five to ten years. In particular, combining home robots and wearable technology is likely to be a key step toward achieving the goal of effectively monitoring patients in the home. These efforts to merge home robots and wearable technology are expected to enable a new generation of complex systems with the ability to monitor subjects' status, facilitate the administration of interventions, and provide an invaluable tool to respond to emergency situations.
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
“Their current capabilities include physiological and biochemical sensing, as well as motion sensing [6,7].”
From A review of wearable sensors and systems with application in rehabilitation (2012) · cites this paper as [7]
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
Unified Parkinson's Disease Rating Scale
(2012) · Springer eBooks · doi:10.1007/springerreference_184495 · Cited by 3,071
Recent Developments in Parkinson's Disease
Hurtig, H. I. (1987) · Neurology · doi:10.1212/wnl.37.5.893 · Cited by 1,925
Jovanov, E., Milenković, A., Otto, C., & de Groen, P. C. (2005) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-2-6 · Cited by 1,013
Gait variability: methods, modeling and meaning
Hausdorff, J. M. (2005) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-2-19 · Cited by 942
Hausdorff, J. M. (2007) · Human Movement Science · doi:10.1016/j.humov.2007.05.003 · Cited by 927
Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm
Bourke, A. K., O’Brien, J., & Lyons, G. M. (2006) · Gait & Posture · doi:10.1016/j.gaitpost.2006.09.012 · Cited by 852
Activity Classification Using Realistic Data From Wearable Sensors
Pärkkä, J., Ermes, M., Korpipää, P., Mäntyjärvi, J., Peltola, J., & Korhonen, I. (2006) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2005.856863 · Cited by 759
Ermes, M., Pärkkä, J., Mäntyjärvi, J., & Korhonen, I. (2008) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2007.899496 · Cited by 707
AMON: A Wearable Multiparameter Medical Monitoring and Alert System
Anliker, U., Ward, J. A., Lukowicz, P., Troster, G., Dolveck, F., Baer, M., Keita, F., Schenker, E. B., Catarsi, F., Coluccini, L., et al. (2004) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2004.837888 · Cited by 707
Monitoring Motor Fluctuations in Patients With Parkinson's Disease Using Wearable Sensors
Patel, S., Lorincz, K., Hughes, R., Huggins, N., Growdon, J., Standaert, D., Akay, M., Dy, J., Welsh, M., & Bonato, P. (2009) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2009.2033471 · Cited by 623
Self-citation
Flagged first, then by citations
Research works printed but not linked: 2
- 0, Shimmer
- baechlin, 0, Assistive cueing, context awareness, freezing of gait, Parkinson's disease, personal health assistant, IEEE Trans Inf Technol Biomed
Cited by
Sorted by citations
Items 401–423 of 423
Vert, A., Weber, K. S., Thai, V., Turner, E., Beyer, K. B., Cornish, B. F., Godkin, F. E., Wong, C., McIlroy, W. E., & Ooteghem, K. V. (2022) · Figshare · doi:10.6084/m9.figshare.19807990
Molano, N. F. N., Castrillon, D. S., & Coronel, F. A. (2025) · Reports — Medical Cases Images and Videos · doi:10.3390/reports9010006
Murphy, B. B., & Torita, T. (2026) · Journal of Analytical Science & Technology · doi:10.1186/s40543-025-00515-y
Sanchez, J. R. S., & Falcón, G. (2025) · Congreso Internacional de Innovación y Tendencias en Ingeniería (CONIITI) · doi:10.1109/coniiti68560.2025.11366143
Nadendla, U. S., Yang, A. P., Weiner, L. G., Pan, D., & Chowdhury, S. K. (2025) · International Conference on Intelligent Computing and Systems at the Edge (ICEdge) · doi:10.1109/icedge67252.2025.11412880
Wearable sensors for respiratory protection in occupational settings
Devkota, J., & Sharma, H. N. (2026) · Journal of Safety Research · doi:10.1016/j.jsr.2026.02.006
State of the art overview wearable glucose sensors based on nanosheets
Li, K., Liu, C., Li, Q., Tian, Z., Shi, H., Li, H., & Zhang, S. (2026) · Materials Today Advances · doi:10.1016/j.mtadv.2026.100751
Smart Wearable Device with Multi-Sensor Integration for Search and Rescue Operations
Pravallika, K., Varshini, P., Goud, G. V., & Srinivas, S. (2025) · International Conference on Advances in Computation, Communication and Information Technology (ICAICCIT) · doi:10.1109/icaiccit68829.2025.11434464
Beldame, J., Civinini, A., Brevet, P., Kloek, N., Gillot, T., Lalevée, M., & Mélone, M.-A. (2026) · Orthopaedics & Traumatology Surgery & Research · doi:10.1016/j.otsr.2026.104689
Alonso-Rollán, S., Márquez-Sánchez, S., Robles-García, M., Alonso, M. B., & Carrera, A. (2025) · Logic Journal of IGPL · doi:10.1093/jigpal/jzaf077
Neurorehabilitation and AI-Driven Cognitive Therapy
Mavai, A. S., Mishra, D. K., & Sharma, A. (2026) · Cognitive systems monographs · doi:10.1007/978-3-032-18782-6_8
A Micro-Vibration-Based Spinal Health Analyzer for Wearable Biomechanical Assessment
Dhavamani, K., Vidhya, M., Indradevi, P., Gayathiri, A., R, D. C., & Hemaraj, M. (2026) · International Conference on Artificial Intelligence and Machine Learning Applications Theme: Healthcare and Internet of Things (AIMLA) · doi:10.1109/aimla67915.2026.11522512
Piezoresistive anlaysis of PVDF-CNF membrane
Laloriya, A., Khanduri, P., & Panwar, V. (2026) · AIP conference proceedings · doi:10.1063/5.0348320
An embedded Cost-effective Wearable Platform for Real Time Monitoring of Physiological Vital Signs
Sinthia, P. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-30008-9_47
Chemistry‑Driven Engineering of PEDOT:PSS Hydrogels for Next‑Generation Bioelectronic Interfaces
Khan, B., Ali, Z., Khalid, R. T., Sajid, A., Fatima, A., Umar, Y., Masrur, M. A., Fatima, K., Mehmood, M., Jan, H., et al. (2026) · Advanced Materials Technologies · doi:10.1002/admt.71182
Selvanayagi, A., Nirmala, R., K, N. A., & Shivani Rajalakshmi, K. (2026) · International Conference on Sustainable Computing and Smart Systems (ICSCSS) · doi:10.1109/icscss69635.2026.11646077
Wei, V. W., Chen, X., Li, J., Wang, Z., 王锡淦, Yin, Z., Wang, L., & Liao, C. (2026) · Med-X · doi:10.1007/s44258-026-00092-8
GyroStep: A Portable IMU-Based System for Knee Flexion Measurement and Real-Time Analysis
Korbel, J., Frącczak, Ł., & Piasecka, K. (2026) · International Conference on Methods and Models in Automation and Robotics · doi:10.1109/mmar70562.2026.11667872
Integrated Wearable Sensor Technologies for Real-Time Sports Performance Evaluation
Srivastava, P., & Biswas, S. (2026) · Wireless Sensor Network · doi:10.4236/wsn.2026.182002
Arriaga, K. M. C., Amador, R. R., Cortés-Maldonado, R., Bueno, C., & Hernández, H. P. M. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-37444-8_22
Lai, L., Arshad, M. R. B., Zou, J., & Lei, C. (2026) · Asian Control Conference (ASCC) · doi:10.1109/ascc70886.2026.11701927
Early Diagnosis of Chronic Diseases Using AI-Enabled Wearable Devices
Singh, G., Sharma, N., & Singh, N. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-2600-2393-8.ch011
A Wearable Electrocardiogram Recorder (ECG) Using ISO / IEEE 11073 Interoperability Standard
Led, S., Martinez-Espronceda, M., Redondo, J., Baquero, A., Niegowski, M., Serrano, L., & Cabezas, L. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-35395-6_25
Metadata
- Authors
- Bonato, P.
- Affiliations
- Harvard University (US)
- Corresponding author
- Bonato, Paolo
- ORCID
- Bonato, Paolo
- Venue
- IEEE Engineering in Medicine and Biology Magazine
- Published
- 2010-05
- Volume
- 29
- Issue
- 3
- Pages
- 25-36
- ISSN
- 0739-5175 (ISSN-L)
- OpenAlex
- W2032802664
- Cited by
- 423
- References
- 66
- Citations by year
- 2026: 22 · 2025: 30 · 2024: 26 · 2023: 15 · 2022: 29 · 2021: 25 · 2020: 29 · 2019: 13 · 2018: 31 · 2017: 29 · 2016: 40 · 2015: 36 · 2014: 38 · 2013: 22 · 2012: 23
- FWCI
- 11.35
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Locations
- IEEE Engineering in Medicine and Biology Magazine (publishedVersion)
- PubMed (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
- Keywords
- wearable sensors, home monitoring, remote patient monitoring, home robots, congestive heart failure, diabetes prevention, Parkinson's disease, epilepsy, cardiac arrest, cardiovascular monitoring, emergency response
- MeSH terms
- Clothing, Diagnosis, Computer-Assisted, Equipment Design, Signal Processing, Computer-Assisted, Telemedicine, Monitoring, Ambulatory
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