A Preliminary Investigation of Monitoring ADLs Using Wireless Kinematic Sensors.

The objective of this on-going work is to evaluate the accuracy and reliability of wireless kinematic sensors in identifying basic activities of daily living (ADL). A preliminary trial was conducted consisting of 5 subjects; 3 male (mean: 23.6, SD: 2.41). Four kinematic sensors were placed on the subject; (a) mid sternum, (b) underneath the left armpit, (c) above the right hip and (d) the ankle of the dominant leg. A fifth sensor, the activPAL™ Trio Professional physical activity logger was used for comparison with the kinematic sensors. Each subject performed a range of basic activities' in a controlled laboratory setting. Subjects were then asked to carry out similar self annotated activities in a random order and in an unsupervised environment. Feature sets of mean, standard deviation, frequency-domain entropy, discrete FFT coefficient and signal magnitude area are being calculated. These feature sets will be used to train several classifiers including decision tree's, nearest neighbor, naive Bayes and support vector machines. Several meta-level classifiers will also be evaluated including boosting, bagging and plurality voting. We aim to identify the most reliable classifier and location for the kinematic sensor in indentifying basic ADLs.