ReviewQuantified self and human movement: A review on the clinical impact of wearable sensing and feedback for gait analysis and intervention
Introduction
The miniaturization of sensing, feedback, and computational devices has opened a new frontier for gait analysis and intervention. Wearable systems are portable and can enable individuals with a variety of movement disorders to benefit from analysis and intervention techniques that have previously been confined to research laboratories and medical clinics. Consumer demand for wearable computational devices such as smart phones has driven down the cost of sensing and actuation components, while simultaneously pushing technological development to enable long-term (hours and days) of continuous use. Thus, there is increasing potential for wearable sensing and feedback systems to provide significant clinical benefits to the broader population.
Increasingly, individuals are joining societal movements such as quantified self [1], life log [2], and Sousveillance [3] and amassing large amounts of personal information through automated wearable systems. In addition, as the distribution of commercial wearable systems, such as Nike + Fuelband, FitBit, Jawbone UP and Google Glass, spreads, societies are moving toward a point where the tracking and feedback of daily information related to walking, working, eating, and sleeping is standard. One aspect of this technological transformation which holds particular interest is that of wearable systems for clinical gait assessment and intervention.
Wearable sensing has long been suggested as a means of measuring human movements [4]. Recent technological advances have produced sensors that are smaller, lighter, and more robust than previous versions and are often combined with portable computation devices, such as smartphones, for a variety of applications [5]. The small size and light weight of accelerometers, gyroscopes, and magnetometers make these a convenient and practical choice for mobile measurements, and the combined packaging of accelerometers and gyroscopes in an inertial measurement unit [6] or accelerometers, gyroscopes, and magnetometers in a magnetometer-accelerometer-rate-gyro [7] have further facilitated the ease-of-use. These advances have enabled new opportunities, not previously possible, to utilize technology for human movement analysis and intervention. Simple systems involving a single accelerometer or a foot switch have been used to detect various spatiotemporal parameters such as step count, stride length, cadence, and walking speed [8], [9], [10], [11], while more complex systems have been created with arrays of accelerometers, gyroscopes, and magnetometers worn across the body to measure joint and segment kinematics [6], [12], [13], [14].
While wearable sensing enables gait assessment, wearable feedback facilitates gait intervention. Wearable haptic (touch) feedback has been used to facilitate gait changes in foot progression angle [15], tibia angle [16], and medio-lateral trunk tilt [16], [17], [18]. Wearable haptic feedback has also been used to alter knee loading patterns during gait by alerting users of center of pressure values [19] or knee loading measurements [20]. Wearable auditory feedback has been used to improve balance through modifying trunk displacement [21].
Although more and more people are incorporating wearable systems into their daily lives, the clinical applications providing societal benefits of these systems are unclear. We undertook this review to determine the clinical applications of wearable sensing and feedback for human gait assessment and intervention. Analysis of these applications could suggest future research in which wearable systems could benefit society by enhancing mobility, and treating and preventing neuromusculoskeletal disease.
Section snippets
Literature search strategy
A literature search was performed for articles published through March 6, 2013 using the following databases: Medline (1950-), Science Citation Index Expanded (SCI-EXPANDED) (1900-), Cumulative Index to Nursing and Allied Health Literature (CINAHL) (1981-), and Cochrane Central Register for Controlled Trials (COCHRANE) (1966-). The search focused on retrieving articles that included the following elements: wearable AND gait AND (sensing OR feedback) (see Table 1 for specific search terms). The
Results
In total, 1344 articles were retrieved from the literature search (Fig. 1). A critical examination of the titles and abstracts using the pre-determined inclusion and exclusion criteria produced 116 remaining articles, and the full text review ultimately yielded 76 articles that satisfied all the inclusion criteria. The publication dates of included articles spanned from 1969 to 2013, and 70% of the articles were published in the last 10 years.
The majority of articles involved testing on healthy
Discussion
The purpose of this review was to assess clinical applications of wearable sensing and feedback for human gait and to identify areas of future research. Four themes emerged, namely the use of wearable systems for: identifying movement disorders; assessing surgical outcomes; improving walking stability; and reducing joint loading. Wearable systems research to date has focused more on analysis and less on intervention as only a small fraction of the articles involved wearable feedback (Fig. 2).
Future work
Wearable systems offer an inherent advantage over grounded laboratory equipment; they are portable and can thus be used outside of the laboratory in humans’ natural environment. Laboratory experiments are beneficial in that they are typically well-controlled, but they may not always be able to recreate real-life scenarios. For example, Strohrmann et al. [25] used wearable sensing to assess the kinematic effects of fatigue in runners on a treadmill in a laboratory and on an outdoor track. They
Authors’ contribution
All authors have made substantial contributions to the following: (1) the conception and design of the study, or acquisition of data, or analysis and interpretation of data, (2) drafting the article or revising it critically for important intellectual content, (3) final approval of the version to be submitted. Each of the authors has read and concurs with the content in the manuscript. The manuscript and the material within have not been and will not be submitted for publication elsewhere.
Conflict of interest
None of the authors had any conflict of interest regarding this manuscript.
Acknowledgments
The authors would like to thank Dr. Julien Favre for his helpful feedback on revising and restructuring this review. This work was supported by the National Basic Research Program (973 Program) of China (Grant No. 2011CB013305), the National Natural Science Foundation of China (Grant No. 51121063), and the U.S. National Science Foundation through the Human-Centered Computing program, grant #1017826.
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