Time-Frequency Based Features for Classification of Walking Patterns

The analysis of gait data has been a challenging problem and several new approaches have been proposed in recent years. This paper describes a novel front-end for classification of gait patterns using data obtained from a tri-axial accelerometer. The novel features consist of delta features, low and high frequency signal variations and energy variations in both frequency bands. The back-end of the system is a Gaussian mixture model based classifier. Using Bayesian adaptation, an overall classification accuracy of 96.1 % was achieved for five walking patterns in six subjects. Index Terms—Gait patterns, accelerometry, ambulatory monitoring, Gaussian mixture model

A nonlinear dynamic model for heart rate response to treadmill walking exercise

A nonlinear dynamic model for heart rate response to treadmill walking exercise, Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE, 22-26 Aug. 2007]. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Technology, Sydney's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it A nonlinear dynamic model for heart rate response to treadmill walking exercise Teddy M. Cheng, Andrey V. Savkin, Branko G. Celler, Lu Wang, Steven W. Su Abstract-A dynamic model of the heart rate response to treadmill walking exercise is presented. The model is a feedback interconnected system; the subsystem in the forward path represents the neural response to exercise, while the subsystem in the feedback path describes the peripheral local response. The parameters of the model were estimated from 5 healthy adult male subjects, each undertaking 3 sets of walking exercise at different speeds. Simulated responses from the model closely match the experimental data both in the exercise and the recovery phases. The model will be useful in explaining the cardiovascular response to exercise and in the design of exercise protocols for individuals

Designing Adaptive Integral Sliding Mode Control for Heart Rate Regulation During Cycle-Ergometer Exercise Using Bio-feedback

Abstract-This paper considers our developed control system which aims to regulate the exercising subjects' heart rate (HR) to a predefined profile. The controller would be an adaptive integral sliding mode controller. Here it is assumed that the controller commands are interpreted as biofeedback auditory commands. These commands can be heard and implemented by the exercising subject as a part of the control-loop. However, transmitting a feedback signal while the pedals are not in the appropriate position to efficiently exert force may lead to a cognitive disengagement of the user from the feedback controller. To address this problem this paper will employ a different form of control system regarding as "actuator-based event-driven control system". This paper will claim that the developed event-driven controller makes it possible to effectively regulate HR to a predetermined HR profile

Falls Management: Detection and Prevention, Using a Waist Mounted Tri-axial Accelerometer

Abstract-We describe a distributed falls management system capable of real-time falls detection in an unsupervised living context and remote longitudinal tracking of falls risk parameters using a waist-mounted triaxial accelerometer. A self-administrable falls risk assessment is used to facilitate falls prevention. A web-interface allows clinicians to monitor the status of individuals and track their compliance with exercise interventions. Early identification of increased falls risk allows targeted interventions to be promptly administered. Real-time detection of falls allows immediate emergency response protocols to be deployed, reducing morbidity and increasing the independence of the community-dwelling elderly community

Multi-Loop Integral Control-Based Heart Rate Regulation for Fast Tracking and Faulty-Tolerant Control Performance in Treadmill Exercises

In order to offer a reliable, fast, and offset-free tracking performance for the regulation of heart rate (HR) during treadmill exercise, a two-input single-output (2ISO) control system by simultaneously manipulating both treadmill speed and gradient is proposed. The decentralized integral controllability (DIC) analysis is extended to nonlinear and non-square processes especially for a 2ISO process, namely multi-loop integral controllability (MIC). The proposed multi-loop integral control-based HR regulation by manipulating treadmill speed and gradient is then validated through a comparative treadmill experiment that compares the system performance of the proposed 2ISO MIC control loop with that of single-input single-output (SISO) loops, speed/gradient-to-HR. The experimental validation presents that by simultaneously using two control inputs, the automated system can achieve the fastest HR tracking performance and stay close to the reference HR during steady state, while comparing with two SISO structures, and offer the fault-tolerant ability if the gains of the two multi-loop integral controllers are well tuned. It has a vital implication for the applications of exercise rehabilitation and fitness in relation to the automated control system