Teddy M. Cheng

Nonlinear Modeling and Control of Human Heart Rate Response During Exercise With Various Work Load Intensities

The first objective of this paper is to introduce a nonlinear system to model the heart rate (HR) response during and after treadmill walking exercise. The model is a feedback interconnected system that has components to describe the central and peripheral local responses to exercise and their interactions. The parameters of the model were experimentally identified from subjects walking on a treadmill at different speeds. The stability of the obtained nonlinear model was mathematically proven. The modeling results demonstrate that the proposed model can be useful in examining the cardiovascular response to exercise. Based on the nonlinear model, the second objective is to present a computer-controlled treadmill system for the regulation of HR during treadmill exercise. The proposed nonlinear controller consists of feedforward and feedback components. The designed control system was experimentally verified and the results demonstrated that the proposed computer-controlled treadmill system regulated the HR of the experimental subjects according to two different exercising HR profiles, indicating that it can play an important role in the design of exercise protocols for individuals.

Detectability and Output Feedback Stabilizability of Nonlinear Networked Control Systems

This paper addresses problems of detectability and output feedback stabilizability of nonlinear systems with sector-type nonlinearities via limited capacity digital communication channels. The main results are given in terms of Riccati algebraic inequalities.

A distributed self-deployment algorithm for the coverage of mobile wireless sensor networks

This letter addresses a coverage problem through the use of a self-deployed mobile wireless sensor network. We propose a distributed motion coordination algorithm for the mobile sensors to autonomously form a sensor barrier between two given landmarks to achieve the barrier coverage. The algorithm is developed based on some simple rules that are computationally efficient and require less communication overhead.

Decentralized control for mobile robotic sensor network self-deployment: Barrier and sweep coverage problems

This paper addresses the problems of barrier coverage and sweep coverage in a corridor environment with a network of self-deployed mobile autonomous robotic sensors. Using the ideas of nearest neighbor rules and information consensus, we propose a decentralized control law for the robotic sensors to solve the coverage problems. Numerical simulations illustrate the effectiveness of the proposed algorithm. The results in this paper demonstrate that such simple motion coordination rules can play a significant role in addressing the issue of coverage in a mobile robotic sensor network.

Decentralized control of a group of mobile robots for deployment in sweep coverage

This paper addresses a problem of sweep coverage by deploying a network of autonomous mobile robots. We propose a decentralized control algorithm for the robots to accomplish the sweep coverage. The sweep coverage is achieved by coordinating the robots to move along a given path that is unknown to the vehicles a priori. The motion coordination algorithm is developed based on simple consensus algorithms. The effectiveness of the algorithm is demonstrated via numerical simulations. The proposed algorithm would have applications to military and civilian operations.

Nonparametric Hammerstein Model Based Model Predictive Control for Heart Rate Regulation

This paper proposed a novel nonparametric model based model predictive control approach for the regulation of heart rate during treadmill exercise. As the model structure of human cardiovascular system is often hard to determine, nonparametric modelling is a more realistic manner to describe complex behaviours of cardiovascular system. This paper presents a new nonparametric Hammerstein model identification approach for heart rate response modelling. Based on the pseudo-random binary sequence experiment data, we decouple the identification of linear dynamic part and input nonlinearity of the Hammerstein system. Correlation analysis is applied to acquire step response of linear dynamic component. Support Vector Regression is adopted to obtain a nonparametric description of the inverse of input static nonlinearity that is utilized to form an approximate linear model of the Hammerstein system. Based on the established model, a model predictive controller under predefined speed and acceleration constraints is designed to achieve safer treadmill exercise. Simulation results show that the proposed control algorithm can achieve optimal heart rate tracking performance under predefined constraints.

Decentralized Control of Mobile Sensor Networks for Asymptotically Optimal Blanket Coverage Between Two Boundaries

We study a problem of blanket coverage by employing a network of self-deployed, autonomous mobile sensors or agents. The coverage problem is to drive the mobile sensor network to form a sensor lattice that completely covers a two-dimensional (2-D) region between two boundaries. In particular, the sensors form into the so-called triangular lattice pattern, and it is optimal in terms of the minimum number of sensors required for complete coverage of a bounded 2-D set. A distributed motion coordination algorithm is proposed for the mobile sensors to address the coverage problem. The algorithm is developed based on some simple consensus algorithms that only rely on local information. To illustrate the proposed algorithm, numerical simulations have been carried out for a number of scenarios.

Optimizing Heart Rate Regulation for Safe Exercise

Safe exercise protocols are critical for effective rehabilitation programs. This paper aims to develop a novel control strategy for an automated treadmill system to reduce the danger of injury during cardiac rehabilitation. We have developed a control-oriented nonparametric Hammerstein model for the control of heart rate during exercises by using support vector regression and correlation analysis. Based on this nonparametric model, a model predictive controller has been built. In order to guarantee the safety of treadmill exercise during rehabilitation, this new automated treadmill system is capable of optimizing system performance over predefined ranges of speed and acceleration. The effectiveness of the proposed approach was demonstrated with six subjects by having their heart rate track successfully a predetermined heart rate.

Transient and steady state estimation of human oxygen uptake based on noninvasive portable sensor measurements

The main motivation of this study is to establish an ambulatory cardio-respiratory analysis system for the monitoring and evaluation of exercise and regular daily physical activity. We explored the estimation of oxygen uptake by using noninvasive portable sensors. These sensors are easy to use but may suffer from malfunctions under free living environments. A promising solution is to combine sensors with different measuring mechanisms to improve both reliability and accuracy of the estimation results. For this purpose, we selected a wireless heart rate sensor and a tri-axial accelerometer to form a complementary sensor platform. We analyzed the relationship between oxygen uptake measured by gas analysis and data collected from the simple portable sensors using multivariable nonlinear modeling approaches. It was observed that the resulting nonlinear multivariable model could not only achieve a better estimate compared with single input single output models, but also had greater potential to improve reliability.

Decentralized robust set-valued state estimation in networked multiple sensor systems

This paper addresses a decentralized robust set-valued state estimation problem for a class of uncertain systems via a data-rate constrained sensor network. The uncertainties of the systems satisfy an energy-type constraint known as an integral quadratic constraint. The sensor network consists of spatially distributed sensors and a fusion center where set-valued state estimation is carried out. The communications from the sensors to the fusion center are through data-rate constrained communication channels. We propose a state estimation scheme which involves coders that are implemented in the sensors, and a decoder-estimator that is located at the fusion center. Their construction is based on the robust Kalman filtering techniques. The robust set-valued state estimation results of this paper involve the solution of a jump Riccati differential equation and the solution of a set of jump state equations.