Conference proceeding
Measuring changes in gait and vehicle transfer ability during inpatient rehabilitation with wearable inertial sensors
2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Vol.2017, pp.425-430
03/2017
Handle:
https://hdl.handle.net/2376/112312
Abstract
Restoration of functional independence in gait and vehicle transfer ability is a common goal of inpatient rehabilitation. Currently, ambulation changes tend to be subjectively assessed by clinicians. To investigate more precise objective assessment of progress in inpatient rehabilitation, we quantitatively assessed gait and transfer performances over the course of rehabilitation with wearable inertial sensors for 20 patients receiving inpatient rehabilitation services. Participant performance was recorded on a sequence of ambulatory tasks that closely resemble everyday activities. We developed a custom software system to process sensor signals and compute metrics that characterize ambulation performance. We quantified changes in gait and transfer ability by performing a repeated measures comparison of the metrics one week apart. Metrics showing the greatest improvement are walking speed, stride regularity, acceleration root mean square, walking smoothness, shank peak angular velocity, and shank range of motion. Wearable sensor-derived metrics can potentially provide rehabilitation therapists with additional valuable information to aid in treatment decisions.
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Details
- Title
- Measuring changes in gait and vehicle transfer ability during inpatient rehabilitation with wearable inertial sensors
- Creators
- Vladimir Borisov - Voiland Sch. of Chem. & Bioeng., Washington State Univ., Pullman, WA, USAGina Sprint - Sch. of Electr. Eng. & Comput. Sci., Washington State Univ., Pullman, WA, USADiane Cook - Sch. of Electr. Eng. & Comput. Sci., Washington State Univ., Pullman, WA, USADouglas Weeks - St. Luke's Rehabilitation Inst., Spokane, WA, USA
- Publication Details
- 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), Vol.2017, pp.425-430
- Academic Unit
- Electrical Engineering and Computer Science, School of
- Publisher
- IEEE
- Identifiers
- 99900547668301842
- Language
- English
- Resource Type
- Conference proceeding