Effect of Sensor Size, Number and Position under the Foot to Measure the Center of Pressure (CoP) Displacement and Total Center of Pressure (CoPT) Using an Anatomical Foot Model.

Ambulatory instrumented insoles are widely used in real-time monitoring of the plantar pressure in order to calculate balance indicators such as Center of Pressure (CoP) or Pressure Maps. Such insoles include many pressure sensors; the required number and surface area of the sensors used are usually determined experimentally. Additionally, they follow the common plantar pressure zones, and the quality of measurement is usually strongly related to the number of sensors. In this paper, we experimentally investigate the robustness of an anatomical foot model, combined with a specific learning algorithm, to measure the static displacement of the center of pressure (CoP) and the center of total pressure (CoPT), as a function of the number, size, and position of sensors. Application of our algorithm to the pressure maps of nine healthy subjects shows that only three sensors per foot, with an area of about 1.5 × 1.5 cm2, are needed to give a good approximation of the CoP during quiet standing when placed on the main pressure areas.

Multiparametric Remote Investigation in the near-IR through Optical Fiber for In Situ Measurements.

Diffuse reflectance spectroscopy (DRS) has proven to be a powerful, reliable, and non-invasive optical method for characterizing a specimen. Nevertheless, these methods are based on a rudimentary interpretation of the spectral response and can be irrelevant to understanding 3D structures. In this work, we proposed adding optical modalities into a customized handheld probe head in order to increase the number of parameters in DRS acquired from the light/matter interaction. It consists of (1) placing the sample in a reflectance manual rotation stage to collect spectral backscattered angularly resolved light and (2) illuminating it with two sequential linear polarization orientations. We demonstrate that this innovative approach leads to a compact instrument, capable of performing fast polarization-resolved spectroscopic analysis. Due to the significant amount of data available with this technique in a short time, we observe sensitive quantitative discrimination between two types of biological tissue provided by a raw rabbit leg. We believe that this technique can pave the way for rapid meat quality check or biomedical diagnosis of pathological tissues in situ at an early stage.

Pulse rate analysis in case of central sleep apnea: a new algorithm for cardiac rate estimation.

This paper first describes the AM-FM demodulation of an arterial pressure signal. Although it is known to be efficient on signals modulated by breathing, we demonstrate that in case of lack of respiratory modulation (real or simulated central sleep apnea), the AM-FM algorithm doesn't perform well in heart rate extraction. We introduce then a new algorithm based on Singular Spectrum Analysis eigenvalues which performs better cardiac frequency estimation in this context. Respiratory estimation is possible but is beyond the scope of this paper. The error for cardiac frequency estimation is around 0.2 BPM (Beats Per Minute) versus 5.5 BPM for the AM-FM demodulation. Further experimentations will be performed (with this time both cardiac and respiratory assessments) and will deal with real sleep apnea cases.

A simple and efficient algorithm with a coarse to fine approach for arterial beat pulse detection.

This paper presents a simple algorithm for arterial beat pulse detection. It consists in a coarse to fine approach : the first step is performed with a lifting Haar wavelet transform with thresholding and provides search intervals, the second step is to localize the beat pulse in the original signal within these areas. Thanks to online available database, the performance of this algorithm can be compared to others and its ability to detect peaks is sufficient considering its low amount of calculation.