Improved Multichannel Electromyograph Using Off-the-Shelf Components for Education and Research.

Most students and researchers with limited funding are often looking for simple and low-cost devices for the acquisition of the electromyogram signal (EMG) in an educational or research setting. Thus, off-the-shelf devices are used and they have already been described in the literature, but they are used without considering their real performances, which are, in general, quite poor from the electronic and signal processing points of view. It is the purpose of this communication to present the evidence of these issues, and to describe an improved version of the "classical" duo, composed of the common ECG/EMG Olimex board and the Arduino microprocessor board. In this case, the Arduino-DUE is used. Three main points are highlighted in this paper: (a) the bandpass characteristics of the ECG/EMG Olimex board and how they can be improved to cope with EMG bandwidth requirements; (b) the increase in sampling frequency of the signal; and, finally, (c) the possibility of automatic detection of more ECG/EMG Olimex boards installed at the same time as the shields on the Arduino-DUE board. Very simple and low-cost modifications on the ECG/EMG Olimex board could deliver a much better performing multichannel EMG acquisition system, suitable for educational classroom experiments and early proof-of-concept research.

A New Algorithm for Estimating a Noiseless, Evenly Sampled, Heart Rate Modulating Signal.

Heart rate variability (HRV) is commonly intended as the variation in the heart rate (HR), and it is evaluated in the time and frequency domains with various well-known methods. In the present paper, the heart rate is considered as a time domain signal, at first as an abstract model in which the HR is the instantaneous frequency of an otherwise periodic signal, such as with an electrocardiogram (ECG). In this model, the ECG is assumed to be a frequency modulated signal, or carrier signal, where HRV or HRV(t) is the time-domain signal which is frequency modulating the carrier ECG signal around its average frequency. Hence, an algorithm able to frequency demodulate the ECG signal to extract the signal HRV(t) is described, with possibly enough time resolution to analyse fast time-domain variations in the instantaneous HR. After exhaustive testing of the method on simulated frequency modulated sinusoidal signals, the new procedure is eventually applied on actual ECG tracings for preliminary nonclinical testing. The purpose of the work is to use this algorithm as a tool and a more reliable method for the assessment of heart rate before any further clinical or physiological analysis.