Several methods have been discussed to assess and quantify proprioceptive deficits. Most clinical assessments are based on categorical or ordinal results which are not sensitive to subtle changes or subtle deficits observed in different patients. In this paper, we propose a quantitative protocol for post-stroke proprioceptive assessment based on three-dimensional inertial tracking. The system is based on a network of five inertial sensors that are attached to the subjects' upper limbs. Validation of our approach was based on a set of upper-limb experiments performed by thirty healthy subjects and six stroke patients. Three angles for the shoulder joint and three angles for the elbow joint were evaluated in a randomized manner. While blindfolded, the volunteers were instructed to move the non-dominant (for healthy subjects) or the affected limb (for stroke subjects) to a target angle, and then were instructed to replicate the contralateral movement. The results obtained from the healthy group were used to establish a baseline for proprioceptive normality and comparisons. Finally, the results of the stroke group were also compared with standard clinical scales. Our findings suggest that the quantitative measure provided by our approach can be much more sensitive to subtle variations in proprioceptive variations than standard clinical scales.
Resumo-Com o intuito de complementar a formação de engenheiros, hoje em dia são organizados torneios de robôs seguidores de linha, como o Torneio Universitário de Robótica. Entretanto, durante edições anteriores do evento, ocorreram diversos problemas relacionados ao uso de fios nos sensores de passagem dos robôs, que demarcam o tempo dos mesmo durante o percurso. Tendo isso em vista, este trabalho propõe um modelo de sensoriamento do trajeto utilizando comunicação por radiofrequência. Cada sensor presente no trajeto é composto por um sensor infravermelho, um microcontrolador e um transponder de radiofrequência. Os dados vindos de cada sensor é enviado ao computador através do Host por meio de uma rede WBAN e posteriormente são plotados numa interface gráfica para serem exibidos para os jurados e o público do evento. Após diversos testes com o sistema, constatou-se que o mesmo é adequado para uso durante o TUR.
Electromyographic signals (EMG) are widely used in Human Machine Interface applications, in the control of myoelectric prostheses and in the control of models in virtual reality environments. To do so, it is necessary to process the EMG signals in order to extract the necessary information for each application. One of the key steps in the processing of EMG signals is the accurate detection of the beginning and end of muscle contractions. Thus, it is necessary to use methods and algorithms that aim to accurately detect onset and offset times of muscle activity, using techniques that involve the calculation of the signal envelope, calculation of thresholds and digital filters. The present work aims at the development of a system capable of performing the acquisition and plotting of EMG signals, as well as onset and offset detection of muscle activity. The system is consisted of hardware, in order to acquire the signal, and software, which is based on parallel processing for real-time detection. The processing method proposed consists in the application of the Hilbert transform with a low-pass filter to calculate the envelope. There was tested two approaches for the smoothing of the rectified signal, being the moving average algorithm the one which showed better results. The methods used in this work present satisfactory results even in a computer with lower power processing, besides it was developed in a reusable way, allowing the interaction with other software applications.
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