Objective: Parkinsonian gait is a defining feature of Shaking Palsy (SP) and it has one of the worse impact on human healthy life than other SP symptoms. The objective of this work is to propose a Parkinsonian gait detection system based on an S-band perception technique to classify abnormal gait and normal walking.
The correct evaluation of the healing process is important to define proper times of fixator dynamization and removal, avoiding refractures. Unfortunately, a quantitative healing assessment is not yet available in clinical practice.
This paper examines how features extracted from full-day data recorded by wearable sensors are able to differentiate between infants with typical development and those with or at risk for developmental delays.
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