Journal article
Analyzing Sensor-Based Time Series Data to Track Changes in Physical Activity during Inpatient Rehabilitation
Sensors (Basel, Switzerland), Vol.17(10), p.2219
09/27/2017
Handle:
https://hdl.handle.net/2376/102904
PMCID: PMC5677114
PMID: 28953257
Abstract
Time series data collected from sensors can be analyzed to monitor changes in physical activity as an individual makes a substantial lifestyle change, such as recovering from an injury or illness. In an inpatient rehabilitation setting, approaches to detect and explain changes in longitudinal physical activity data collected from wearable sensors can provide value as a monitoring, research, and motivating tool. We adapt and expand our Physical Activity Change Detection (PACD) approach to analyze changes in patient activity in such a setting. We use Fitbit Charge Heart Rate devices with two separate populations to continuously record data to evaluate PACD, nine participants in a hospitalized inpatient rehabilitation group and eight in a healthy control group. We apply PACD to minute-by-minute Fitbit data to quantify changes within and between the groups. The inpatient rehabilitation group exhibited greater variability in change throughout inpatient rehabilitation for both step count and heart rate, with the greatest change occurring at the end of the inpatient hospital stay, which exceeded day-to-day changes of the control group. Our additions to PACD support effective change analysis of wearable sensor data collected in an inpatient rehabilitation setting and provide insight to patients, clinicians, and researchers.
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Details
- Title
- Analyzing Sensor-Based Time Series Data to Track Changes in Physical Activity during Inpatient Rehabilitation
- Creators
- Gina Sprint - Department of Computer Science, Gonzaga University, Spokane, WA 99202, USA. sprint@gonzaga.eduDiane Cook - School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99163, USA. cook@eecs.wsu.eduDouglas Weeks - St. Luke's Rehabilitation Institute, Spokane, WA 99202, USA. weeksdl@st-lukes.orgJordana Dahmen - School of Biological Sciences, Washington State University, Pullman, WA 99163, USA. jordana.dahmen@wsu.eduAlyssa La Fleur - Department of Mathematics and Computer Science, Whitworth University, Spokane, WA 99251, USA. alafleur19@my.whitworth.edu
- Publication Details
- Sensors (Basel, Switzerland), Vol.17(10), p.2219
- Academic Unit
- Electrical Engineering and Computer Science, School of
- Publisher
- Switzerland
- Identifiers
- 99900546548201842
- Language
- English
- Resource Type
- Journal article