Introduction to linear and nonlinear programming

Fuzzy logic control was originally introduced and developed as a model free control design approach. However, it unfortunately suffers from criticism of lacking of systematic stability analysis and controller design though it has a great success in industry applications. In the past ten years or so, prevailing research efforts on fuzzy logic control have been devoted to model-based fuzzy control systems that guarantee not only stability but also performance of closed-loop fuzzy control systems. This paper presents a survey on recent developments (or state of the art) of analysis and design of model based fuzzy control systems. Attention will be focused on stability analysis and controller design based on the so-called Takagi-Sugeno fuzzy models or fuzzy dynamic models. Perspectives of model based fuzzy control in future are also discussed

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A Survey on Analysis and Design of Model-Based Fuzzy Control Systems

Myoelectric control systems—A survey

This paper proposes and evaluates the application of support vector machine (SVM) to classify upper limb motions using myoelectric signals. It explores the optimum configuration of SVM-based myoelectric control, by suggesting an advantageous data segmentation technique, feature set, model selection approach for SVM, and postprocessing methods. This work presents a method to adjust SVM parameters before classification, and examines overlapped segmentation and majority voting as two techniques to improve controller performance. A SVM, as the core of classification in myoelectric control, is compared with two commonly used classifiers: linear discriminant analysis (LDA) and multilayer perceptron (MLP) neural networks. It demonstrates exceptional accuracy, robust performance, and low computational load. The entropy of the output of the classifier is also examined as an online index to evaluate the correctness of classification; this can be used by online training for long-term myoelectric control operations.

Support Vector Machine-Based Classification Scheme for Myoelectric Control Applied to Upper Limb

Apparatus and methods are provided for use with a subject who is undergoing respiration. A motion sensor senses motion of a subject. A breathing pattern analysis unit analyzes components of the sensed motion that result from the subject's respiration. The breathing pattern analysis unit includes double-movement-respiration-cycle-pattern-identification functionality that designates respiration cycles as being double-movement-respiration-cycles (DMRC's) by determining that the cycles define two subcycles. Double-movement-respiration-cycle-event-identification functionality of the breathing pattern analysis unit identifies a DMRC event by detecting that the subject has undergone a plurality of DMRC's. An output is generated that is indicative of the subject having used accessory muscles in breathing, in response to identification of the double-movement-respiration-cycle event. Other embodiments are also described.

Monitoring, predicting and treating clinical episodes

A monitoring system (10) of this invention includes a first sensor (12) for detecting the respiration and/or movements of an infant (14), and an optional second sensor (18) for detecting the presence and/or movement of the infant or proximal objects (20) surrounding the infant. An optional accelerometric sensor (22) detects movements of a platform (16) supporting the infant and contributes supplementary movement data to the monitoring system. An optional audio sensor (24) detects sounds associated with the infant or proximal objects. None of the sensors are physically attached to the infant. A controller (26) conditions and processes the various sensor signals and generates alarms by interpreting the sensor signals. The controller optionally communicates with a remote control unit (30). In one embodiment the first sensor signal is filtered (112, 114) to extract respiration- and nonrespiration-related signals that are processed by a signal processor (116), which compares the extracted signals to thresholds, and if neither signal exceeds its threshold for a predetermined time, a low signal alarm is generated. In another embodiment, the signal processor determines whether a respiration decay period is less than a threshold value, and if not, generates a respiration decay alarm. In yet another embodiment, the signal processor compares the respiration-related signal pattern to a stored pattern, and if the patterns do not match, a respiration pattern alarm is generated. The signal processor further interprets various combinations of the sensor signals and makes aggregated decisions to generate specific warnings when critical situations occur.

Respiration and movement monitoring system

From the Publisher:
Fuzzy and Neuro-Fuzzy Systems in Medicine provides a thorough review of state-of-the-art techniques and practices, defines and explains relevant problems, as well as provides solutions to these problems. After an introduction, the book progresses from one topic to another - with a linear development from fundamentals to applications.

Fuzzy and Neuro-Fuzzy Systems in Medicine

An object sensing system (10) employs a resonant sensor (20) that receives drive energy coupled from an oscillator (12) operating at a frequency equal or close to the resonant frequency of the resonant sensor. The resonant sensor preferably includes an planar winding (60) that maximizes its distributed inductive and capacitive components, which are sensitive to a proximal conductive, nonconductive, magnetic, or nonmagnetic object (22). The resonant sensor is electrically connected in one leg of a voltage divider that produces a changing output signal voltage in response to resonant frequency changes caused by the object in proximity to the resonant sensor. The signal voltage is amplified, filtered, and processed to extract relevant data indicative of the presence, distance, movement, or proximity of the object.

Position and movement resonant sensor

INTRODUCTION New Technologies in Rehabilitation: General Trends SENSORIAL PROSTHESES A Retinal Prosthesis to Benefit the Visually Impaired Intelligent Techniques in Hearing Rehabilitation LOCOMOTOR PROSTHESES Sensory Feedback for Lower Limb Prostheses Multifunction Control of Prostheses using the Myoelectric Signal Selective Activation of the Nervous System for Motor System Neural Prostheses Upper Limb Myoelectric Prostheses: Sensory Control System and Automatic Tuning of Parameters PACEMAKERS AND LIFE-SUSTAINING DEVICES Computer-Aided Support Technology for Artificial Heart Control: Diagnosis and Hemodynamic Measurements Diaphragm Pacing for Chronic Respiratory Insufficiency Intelligent Systems in Heart Pacemakers ROBOTIC SYSTEMS AND ADVANCED MECHANICS Service Robots for Rehabilitation and Assistance Computerized Obstacle Avoidance Systems for the Blind and Visually Impaired Advanced Design Concepts for a Knee-Ankle-Foot Orthosis Index of Acronyms and Abbreviations Index of Terms

Horia-Nicolai Teodorescu

Papers

Respiration and movement monitoring system

Fuzzy and Neuro-Fuzzy Systems in Medicine

Position and movement resonant sensor

Intelligent systems and technologies in rehabilitation engineering

Using Analytics and Social Media for Monitoring and Mitigation of Social Disasters