The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
On-Shoe Wearable Sensors for Gait and Turning Assessment of Patients With Parkinson's Disease
Open accessAbstract
Assessment of locomotion through simple tests such as timed up and go (TUG) or walking trials can provide valuable information for the evaluation of treatment and the early diagnosis of people with Parkinson's disease (PD). Common methods used in clinics are either based on complex motion laboratory settings or simple timing outcomes using stop watches. The goal of this paper is to present an innovative technology based on wearable sensors on-shoe and processing algorithm, which provides outcome measures characterizing PD motor symptoms during TUG and gait tests. Our results on ten PD patients and ten age-matched elderly subjects indicate an accuracy ± precision of 2.8 ± 2.4 cm/s and 1.3 ± 3.0 cm for stride velocity and stride length estimation compared to optical motion capture, with the advantage of being practical to use in home or clinics without any discomfort for the subject. In addition, the use of novel spatio-temporal parameters, including turning, swing width, path length, and their intercycle variability, was also validated and showed interesting tendencies for discriminating patients in ON and OFF states and control subjects.
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Cites
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Self-citationiTUG, a Sensitive and Reliable Measure of Mobility
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3D gait assessment in young and elderly subjects using foot-worn inertial sensors
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Wearable Sensors for Human Activity Monitoring: A Review
Mukhopadhyay, S. C. (2015) · IEEE Sensors Journal · doi:10.1109/jsen.2014.2370945 · Cited by 1,401
Technology in Parkinson’s disease: challenges and opportunities
Espay, A. J., Bonato, P., Nahab, F. B., Maetzler, W., Dean, J. M., Klucken, J., Eskofier, B. M., Merola, A., Horak, F., Lang, A. E., et al. (2016) · Movement Disorders · doi:10.1002/mds.26642 · Cited by 654
How Wearable Sensors Can Support Parkinson's Disease Diagnosis and Treatment: A Systematic Review
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Continuous Monitoring of Turning in Patients with Movement Disability
El-Gohary, M., Pearson, S., McNames, J., Mancini, M., Horak, F., Mellone, S., & Chiari, L. (2013) · Sensors · doi:10.3390/s140100356 · Cited by 258
Lefeber, N., Degelaen, M., Truyers, C., Safin, I., & Beckwee, D. (2019) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2019.2930751 · Cited by 77
IoT-based Technologies for Addressing the Unique Healthcare Needs of the Elderly Population
Ali, S. A., & Khan, R. (2023) · doi:10.20944/preprints202303.0088.v1 · Cited by 7
Metadata
- Authors
- Mariani, B., Jiménez, M. C., Vingerhoets, F. J. G., & Aminian, K.
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2013-01
- Volume
- 60
- Issue
- 1
- Pages
- 155-158
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- OpenAlex
- W2058190976
- Cited by
- 278
- References
- 14
- FWCI
- 43.31
- Type
- journal article
- Language
- en
- Open access
- green
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