Preliminary investigation of energy comparation between gyroscope, electromyography and VO2 wearable sensors.

Building on previous experiments in the domain of energy expenditure estimation using wearable sensors, the measurements of energy ratios of a runner on a treadmill were analyzed to observe any commonalities between an inertia measurement unit and an electromyograph sensor. The subjects were equipped with a VO2 gas measurement device, an Inertial Measurement Unit (IMU) measuring gyroscopic activity and an electromyography (EMG) sensor network whilst running at 5 different speeds on a calibrated treadmill. The observed results established a co-linear relationship with the gyroscope based measurements, EMG based measurements with the VO2 measurements.

Motion trajectory analysis for evaluating the performance of functional upper extremity tasks in daily living: a pilot study.

Since 1998, tele-rehabilitation has been extensively studied for its potential capacity of saving time and cost for both therapists and patients. However, one gap hindering the deployment of tele-rehabilitation service is the approach to evaluate the outcome after tele-rehabilitation exercises without the presence of professional clinicians. In this paper, we propose an approach to model jerky and jerky-free movement trajectories with hidden Markov models (HMMs).

Multi-kinect skeleton fusion for physical rehabilitation monitoring.

Kinect has been increasingly applied in rehabilitation as a motion capture device. However, the inherent limitations significantly hinder its further development in this important area. Although a number of Kinect fusion approaches have been proposed, only a few of them was actually considered for rehabilitation.

A syntactic two-component encoding model for the trajectories of human actions.

Human actions have been widely studied for their potential application in various areas such as sports, pervasive patient monitoring, and rehabilitation. However, challenges still persist pertaining to determining the most useful ways to describe human actions at the sensor, then limb and complete action levels of representation and deriving important relations between these levels each involving their own atomic components. In this paper, we report on a motion encoder developed for the sensor level based on the need to distinguish between the shape of the sensor's trajectory and its temporal characteristics during execution.

Further applications of Doppler radar for non-contact respiratory assessment.

This paper further investigates the use of Doppler radar for detecting and identifying certain human respiratory characteristics from observed frequency and phase modulations. Specifically, we show how breathing frequencies can be determined from the demodulated signal leading to identifying abnormalities of breathing patterns using signal derivatives, optimal filtering and standard statistical measures. Specifically, we report results on a robust method for distinguishing cessation of the normal breathing cycle.