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| Content Provider | ACM Digital Library |
|---|---|
| Author | Xu, Wenyao Amini, Navid Sarrafzadeh, Majid He, Lei Huang, Ming-Chun Liu, Jason J. |
| Abstract | Gait analysis is an important medical diagnostic process and has many applications in rehabilitation, therapy and exercise training. However, standard human gait analysis has to be performed in a specific gait lab and operated by a medical professional. This traditional method increases the examination cost and decreases the accuracy of the natural gait model. In this paper, we present a novel portable system, called Smart Insole, to address the current issues. Smart Insole integrates low cost sensors and computes important gait features. In this way, patients or users can wear Smart Insole for gait analysis in daily life instead of participating in gait lab experiments for hours. With our proposed portable sensing system and effective feature extraction algorithm, the Smart Insole system enables precise gait analysis. Furthermore, taking advantage of the affordability and mobility of Smart Insole, pervasive gait analysis can be extended to many potential applications such as fall prevention, life behavior analysis and networked wireless health systems. |
| Starting Page | 1 |
| Ending Page | 4 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781450313001 |
| DOI | 10.1145/2413097.2413120 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2012-06-06 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Wireless health Wearable device Gait analysis |
| Content Type | Text |
| Resource Type | Article |
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