Using mobile phones for activity recognition in Parkinson’s patients
- 1Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL, USA
- 2Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, USA
Mobile phones with built-in accelerometers promise a convenient, objective way to quantify everyday movements and classify those movements into activities. Using accelerometer data we estimate the following activities of 18 healthy subjects and eight patients with Parkinson’s disease: walking, standing, sitting, holding, or not wearing the phone. We use standard machine learning classifiers (support vector machines, regularized logistic regression) to automatically select, weigh, and combine a large set of standard features for time series analysis. Using cross validation across all samples we are able to correctly identify 96.1% of the activities of healthy subjects and 92.2% of the activities of Parkinson’s patients. However, when applying the classification parameters derived from the set of healthy subjects to Parkinson’s patients, the percent correct lowers to 60.3%, due to different characteristics of movement. For a fairer comparison across populations we also applied subject-wise cross validation, identifying healthy subject activities with 86.0% accuracy and 75.1% accuracy for patients. We discuss the key differences between these populations, and why algorithms designed for and trained with healthy subject data are not reliable for activity recognition in populations with motor disabilities.
Keywords: mobile phone, accelerometer, activity recognition, Parkinson’s disease
Citation: Albert MV, Toledo S, Shapiro M and Kording K (2012) Using mobile phones for activity recognition in Parkinson’s patients. Front. Neur. 3:158. doi: 10.3389/fneur.2012.00158
Received: 18 April 2012; Accepted: 19 October 2012;
Published online: 07 November 2012.
, Tokushima University Hospital, Japan
Copyright: © 2012 Albert, Toledo, Shapiro and Kording. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.
*Correspondence: Mark V. Albert, Sensory Motor Performance Program, Rehabilitation Institute of Chicago, 345 E Superior Street room 1479, Chicago, IL 60611, USA. e-mail: firstname.lastname@example.org