Alberto López Delis

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This paper presents the development of a bioinstrumentation system for the acquisition and pre-processing of surface electromyographic (SEMG) signals, as well as the proposal of a myoelectric controller for leg prostheses, using algorithms for feature extraction and classification of myoelectric patterns. The implemented microcontrolled bioinstrumentation(More)
Traditional methodologies use electrocardiographic (ECG) signals to develop automatic methods for onset and peak detection on the arterial pulse wave. An alternative method using pattern recognition is implemented to detect onset and peak fiducial points, using Self Organizing Maps (SOM). In the present work SOM neural networks were trained with a dataset(More)
The electromyographic signal is the electrical manifestation of the neuromuscular activation associated with a contracting muscle. The surface electromyographic (SEMG) signal represents the current generated by ionic flow across the membrane of the muscle fibers that propagates through the intervening tissues to reach the detection surface of an electrode(More)
This paper presents a myoelectric knee joint angle estimation algorithm for control of active transfemoral prostheses, based on feature extraction and pattern classification. The feature extraction stage uses a combination of time domain and frequency domain methods (entropy of myoelectric signals and cepstral coefficients, respectively). Additionally, the(More)
A prominent change is being carried out in the fields of rehabilitation and assistive exoskeletons in order to actively aid or restore legged locomotion for individuals suffering from muscular impairments, muscle weakness, neurologic injury, or disabilities that affect the lower limbs. This paper presents a characterization of knee motion patterns from(More)
Rehabilitation of motor function has been linked to motor learning that occurs during repetitive, frequent, and intensive training. Neuro-rehabilitation is based on the assumption that motor learning principles can be applied to motor recovery after injury, and that training can lead to permanent improvements in motor function in patients with motor(More)
This article presents a method to estimate the knee angle based on data fusion for transfemoral leg prostheses control, using information from two electromyographic signals, two gyroscope sensors and one electrogoniometer channel. This information is processed in three stages: feature extraction using cepstral coefficients and the myoelectric signal(More)
This article describes the design of a microcontrolled bioinstrumentation system for active control of leg prostheses, using 4-channel electromyographic signal (EMG) detection and a single-channel electrogoniometer. The system is part of a control and instrumentation architecture in which a master processor controls the tasks of slave microcontrollers,(More)