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1.
Article in English | MEDLINE | ID: mdl-21096751

ABSTRACT

This paper describes the basic guidelines for developing an innovative biomedical device. It covers the issues of researching about a suitable material, developing a new device, and testing its proprieties to check its effectiveness. The goal of the device is to control food flow into the esophagus, reducing its volume and the speed of food intake to help in the treatment of obesity. This module, called Esophageal Flow Controller (EFC®), is made of latex. Three different models of prototypes were developed, and 10 units of each model had their constructive and mechanical characteristics evaluated. All of them have followed the same manufacturing cycle. The results showed that the Esophageal Flow Control module has all the essential characteristics of an effective device for flow control in the esophagus.


Subject(s)
Appetite Regulation , Deglutition/physiology , Esophagus/physiology , Latex/chemistry , Materials Testing , Prosthesis Design , Artificial Organs , Elastic Modulus , Humans , Models, Biological , Obesity/therapy , Prostheses and Implants , Temperature
2.
Article in English | MEDLINE | ID: mdl-21097333

ABSTRACT

This article presents the development of a prototype insole derived from natural rubber from Hevea brasiliensis, equipped with pressure control and capable of neoformation of tissue for people who have diabetic foot. The active element of this insole is the electronic circuit that monitors the plantar pressure. In addition, on the present stage of the research, a signal irradiating cell is used based on the principle of tissue regeneration using laser. This project proposes a "smart" insole prototype with a pressure monitoring system and an electronic system for tissue regeneration, which will open a new approach in an attempt to solve the problem of diabetic foot.


Subject(s)
Diabetic Foot/therapy , Guided Tissue Regeneration/instrumentation , Orthotic Devices , Pressure , Shoes , Biocompatible Materials , Electronics, Medical , Humans , Software
3.
Article in English | MEDLINE | ID: mdl-21095674

ABSTRACT

Despite of its apparent protection by being located deep in a bony canal, the facial nerve is a cranial pair of nerves more vulnerable to traumatic injuries. The surgical accidents are the most frequent causes of intratemporal complications of the facial nerve. Among the postoperative sequelae, the thermal injuries are common due to overheating of the otologic burr resulting in facial paralysis. For the prevention of thermal injuries in the facial nerve was designed a data acquisition board to obtain the temperature measured by thermocouples using a PC and parallel communication. The signals from the temperature sensors passed through conditioning for amplification and analog to digital data conversion. Afterwards, they were stored on a computer for the statistical analysis and the visualization of the curves of variation of the measured temperatures. These curves provide the verification of the facial nerve temperature ascending and descending time during surgery steps to access the nerve. These data provide a substantial safe working margin to the surgeon.


Subject(s)
Decompression, Surgical/instrumentation , Electronics, Medical/instrumentation , Facial Nerve Injuries/diagnosis , Facial Nerve Injuries/surgery , Monitoring, Intraoperative/instrumentation , Signal Processing, Computer-Assisted/instrumentation , Thermometers , Equipment Design , Equipment Failure Analysis , Humans
4.
Physiol Meas ; 30(9): 931-46, 2009 Sep.
Article in English | MEDLINE | ID: mdl-19661566

ABSTRACT

The surface electromyographic (SEMG) signal is very convenient for prosthesis control because it is non-invasively acquired and intrinsically related to the user's intention. This work presents a feature extraction and pattern classification algorithm for estimation of the intended knee joint angle from SEMG signals acquired using two sets of electrodes placed on the upper leg. The proposed algorithm uses a combination of time-domain and frequency-domain approaches for feature extraction (signal amplitude histogram and auto-regressive coefficients, respectively), a self-organizing map for feature projection and a Levenberg-Marquardt multi-layer perceptron neural network for pattern classification. The new algorithm was quantitatively compared with the method proposed by Wang et al (2006 Med. Biol. Eng. Comput. 44 865-72), which uses wavelet packet feature extraction, principal component analysis and a multi-layer perceptron neural classifier. The proposed method provided lower error-to-signal percentage and peak error amplitudes, higher correlation and fewer error events. The algorithm presented in this work may be useful as part of a myoelectric controller for active leg prostheses designed for transfemoral amputees.


Subject(s)
Artificial Limbs , Electromyography/methods , Knee Joint/anatomy & histology , Adult , Algorithms , Data Interpretation, Statistical , Female , Humans , Male , Neural Networks, Computer , Reproducibility of Results , Young Adult
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