A force-sensing platform (FSP), sensitive to changes of the postural control system was designed. The platform measured effects of postural perturbations in static and dynamic conditions. This paper describes the implementation of an FSP using force-sensing resistors as sensing elements. Real-time qualitative assessment utilized a rainbow color scale to identify areas with high force concentration. Postprocessing of the logged data provided end-users with quantitative measures of postural control. The objective of this research was to establish the feasibility of using an FSP to test and gauge human postural control. Tests were conducted in eye open and eye close states. Readings obtained were tested for repeatability using a one-way analysis of variance test. The platform gauged postural sway by measuring the area of distribution for the weighted center of applied pressure at the foot. A fuzzy clustering algorithm was applied to identify regions of the foot with repetitive pressure concentration. Potential application of the platform in a clinical setting includes monitoring rehabilitation progress of stability dysfunction. The platform functions as a qualitative tool for initial, on-the-spot assessment, and quantitative measure for postacquisition assessment on balance abilities.

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This paper presents a general framework of intelligent biofeedback for smart healthcare system and its impact on healthcare of professional athletes, especially during rehabilitation monitoring. The application of machine learning techniques along with various wireless wearable sensors facilitated in building a knowledge base system for healthcare monitoring of the subjects and providing a visual/numeric biofeedback to the clinicians, patients and healthcare professionals. The validated system can potentially be used as a decision supporting tool by the clinicians, physiotherapists, physiatrists and sports trainers for quantitative rehabilitation analysis of the subjects in conjunction with the existing recovery monitoring systems. Based on the results achieved, a conceptual design and model for next generation smart healthcare system/devices for professional athletes has been proposed.

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