Sit2StandPy: Automated Sit-to-Stand Transition Detection¶
Sit2StandPy is an open source Python package that uses novel algorithms to first detect Sit-to-Stand transitions
from lumbar-mounted accelerometer data, and then provide quantitative metrics assessing the performance of the
transitions. A modular framework is employed that would allow for easy modification of parts of the algorithm to suit
other specific requirements, while still keeping core elements of the algorithm intact. As gyroscopes impose a
significant detriment to battery life due to power consumption, Sit2StandPy’s use of acceleration only allows for
a single sensor to collect days worth of analyzable data.
Validation¶
Sit2StandPy was validated, and used to compute the results presented in [1]. Detailed background and
presentation of the methods can be found there as well.
Capabilities¶
- Automatic day by day windowing, with option to select a specific window of hours per day
- Optional use of parallel processing to decrease run time
- Quantification of detected transitions
- Modification of functions and methods used in framework
- Access to various parameters controlling the performance and function of the detection
License¶
Sit2StandPy is open source software distributed under the MIT license.
Papers¶
| [1] |
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| [2] |
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