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      A review of wearable sensors and systems with application in rehabilitation

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          Abstract

          The aim of this review paper is to summarize recent developments in the field of wearable sensors and systems that are relevant to the field of rehabilitation. The growing body of work focused on the application of wearable technology to monitor older adults and subjects with chronic conditions in the home and community settings justifies the emphasis of this review paper on summarizing clinical applications of wearable technology currently undergoing assessment rather than describing the development of new wearable sensors and systems. A short description of key enabling technologies (i.e. sensor technology, communication technology, and data analysis techniques) that have allowed researchers to implement wearable systems is followed by a detailed description of major areas of application of wearable technology. Applications described in this review paper include those that focus on health and wellness, safety, home rehabilitation, assessment of treatment efficacy, and early detection of disorders. The integration of wearable and ambient sensors is discussed in the context of achieving home monitoring of older adults and subjects with chronic conditions. Future work required to advance the field toward clinical deployment of wearable sensors and systems is discussed.

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          Gait assessment in Parkinson's disease: toward an ambulatory system for long-term monitoring.

          Françios J G Vingerhoets, Arash Salarian, Catherine Dehollain … (2004)
          An ambulatory gait analysis method using body-attached gyroscopes to estimate spatio-temporal parameters of gait has been proposed and validated against a reference system for normal and pathologic gait. Later, ten Parkinson's disease (PD) patients with subthalamic nucleus deep brain stimulation (STN-DBS) implantation participated in gait measurements using our device. They walked one to three times on a 20-m walkway. Patients did the test twice: once STN-DBS was ON and once 180 min after turning it OFF. A group of ten age-matched normal subjects were also measured as controls. For each gait cycle, spatio-temporal parameters such as stride length (SL), stride velocity (SV), stance (ST), double support (DS), and gait cycle time (GC) were calculated. We found that PD patients had significantly different gait parameters comparing to controls. They had 52% less SV, 60% less SL, and 40% longer GC. Also they had significantly longer ST and DS (11% and 59% more, respectively) than controls. STN-DBS significantly improved gait parameters. During the stim ON period, PD patients had 31% faster SV, 26% longer SL, 6% shorter ST, and 26% shorter DS. GC, however, was not significantly different. Some of the gait parameters had high correlation with Unified Parkinson's Disease Rating Scale (UPDRS) subscores including SL with a significant correlation (r = -0.90) with UPDRS gait subscore. We concluded that our method provides a simple yet effective way of ambulatory gait analysis in PD patients with results confirming those obtained from much more complex and expensive methods used in gait labs.
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            iTUG, a sensitive and reliable measure of mobility.

            F. B. Horak, Arash Salarian, John G. Nutt … (2010)
            Timed Up and Go (TUG) test is a widely used clinical paradigm to evaluate balance and mobility. Although TUG includes several complex subcomponents, namely: sit-to-stand, gait, 180 degree turn, and turn-to-sit; the only outcome is the total time to perform the task. We have proposed an instrumented TUG, called iTUG, using portable inertial sensors to improve TUG in several ways: automatic detection and separation of subcomponents, detailed analysis of each one of them and a higher sensitivity than TUG. Twelve subjects in early stages of Parkinson's disease (PD) and 12 age matched control subjects were enrolled. Stopwatch measurements did not show a significant difference between the two groups. The iTUG, however, showed a significant difference in cadence between early PD and control subjects (111.1 +/- 6.2 versus 120.4 +/- 7.6 step/min, p < 0.006) as well as in angular velocity of arm-swing (123 +/- 32.0 versus 174.0+/-50.4 degrees/s, p < 0.005), turning duration (2.18 +/- 0.43 versus 1.79 +/- 0.27 s, p < 0.023), and time to perform turn-to-sits (2.96 +/- 0.68 versus 2.40 +/- 0.33 s, p < 0.023). By repeating the tests for a second time, the test-retest reliability of iTUG was also evaluated. Among the subcomponents of iTUG, gait, turning, and turn-to-sit were the most reliable and sit-to-stand was the least reliable.
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              Geographic access to health care for rural Medicare beneficiaries.

              Marcia Hart, Leighton Chan, Christopher D Goodman (2005)
              Patients in rural areas may use less medical care than those living in urban areas. This could be due to differences in travel distance and time and a utilization of a different mix of generalists and specialists for their care. To compare the travel times, distances, and physician specialty mix of all Medicare patients living in Alaska, Idaho, North Carolina, South Carolina, and Washington. Retrospective design, using 1998 Medicare billing data. Travel time was determined by computing the road distance between 2 population centroids: the patient's and the provider's zone improvement plan codes. There were 2,220,841 patients and 39,780 providers in the cohort, including 6,405 (16.1%) generalists, 24,772 (62.3%) specialists, and 8,603 (21.6%) nonphysician providers. There were 20,693,828 patient visits during the study. The median overall 1-way travel distance and time was 7.7 miles (interquartile range 1.9-18.7 miles) and 11.7 minutes (interquartile range 3.0-25.7 minutes). The patients in rural areas needed to travel 2 to 3 times farther to see medical and surgical specialists than those living in urban areas. Rural residents with heart disease, cancer, depression, or needing complex cardiac procedures or cancer treatment traveled the farthest. Increasing rurality was also related to decreased visits to specialists and an increasing reliance on generalists. Residents of rural areas have increased travel distance and time compared to their urban counterparts. This is particularly true for rural residents with specific diagnoses or those undergoing specific procedures. Our results suggest that most rural residents do not rely on urban areas for much of their care.
              Article 0 comments Cited 116 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): J Neuroeng Rehabil
                Journal ID (iso-abbrev): J Neuroeng Rehabil
                Title: Journal of NeuroEngineering and Rehabilitation
                Publisher: BioMed Central
                ISSN (Electronic): 1743-0003
                Publication date Collection: 2012
                Publication date (Electronic): 20 April 2012
                Volume: 9
                Page: 21
                Affiliations
                [1 ]Department of Physical Medicine and Rehabilitation, Harvard Medical School, Spaulding Rehabilitation Hospital, Boston, MA, USA
                [2 ]Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA
                [3 ]Rehabilitation Medicine Department Clinical Center, National Institutes of Health, Bethesda, MD, USA
                [4 ]Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
                [5 ]Department of Physical Therapy and Rehabilitation Science, University of Maryland School of Medicine, Baltimore, MD, USA
                [6 ]National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, USA
                Article
                Publisher ID: 1743-0003-9-21
                DOI: 10.1186/1743-0003-9-21
                PMC ID: 3354997
                PubMed ID: 22520559
                SO-VID: 1d7e1c64-db92-4ab1-b513-c58b703f0f83
                Copyright © Copyright ©2012 Patel et al; licensee BioMed Central Ltd.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 10 October 2011
                Date accepted : 20 April 2012
                Categories
                Subject: Review

                ScienceOpen disciplines: Neurosciences
                Keywords: home monitoring,smart home,wearable sensors and systems,telemedicine
                Data availability:
                ScienceOpen disciplines: Neurosciences
                Keywords: home monitoring, smart home, wearable sensors and systems, telemedicine

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