Donning/Doffing and Arm Positioning Influence in Upper Limb Adaptive Prostheses Control

[EN] New upper limb prostheses controllers are continuously being proposed in the literature. However, most of the prostheses commonly used in the real world are based on very old basic controllers. One reason to explain this reluctance to change is the lack of robustness. Traditional controllers have been validated by many users and years, so the introduction of a new controller paradigm requires a lot of strong evidence of a robust behavior. In this work, we approach the robustness against donning/doffing and arm position for recently proposed linear filter adaptive controllers based on myoelectric signals. The adaptive approach allows to introduce some feedback in a natural way in real time in the human-machine collaboration, so it is not so sensitive to input signals changes due to donning/doffing and arm movements. The average completion rate and path efficiency obtained for eight able-bodied subjects donning/doffing five times in four days is 95.83% and 84.19%, respectively, and for four participants using different arm positions is 93.84% and 88.77%, with no statistically significant difference in the results obtained for the different conditions. All these characteristics make the adaptive linear regression a potential candidate for future real world prostheses controllers.This work is partially supported by Ministerio de Educacion, Cultura y Deporte (Spain) under grant FPU15/02870. The authors would like to thank Lucas Parra for the Myo device and Janne M. Hahne for discussions about the subject of the paper.Igual, C.; Camacho-García, A.; Bernabeu Soler, EJ.; Igual García, J. (2020). Donning/Doffing and Arm Positioning Influence in Upper Limb Adaptive Prostheses Control. Applied Sciences. 10(8):1-19. https://doi.org/10.3390/app10082892S119108Esquenazi, A. (2004). 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Experimental Assessment of Time Reversal for In-Body to In-Body UWB Communications

[EN] The standard of in-body communications is limited to the use of narrowband systems. These systems are far from the high data rate connections achieved by other wireless telecommunication services today in force. The UWB frequency band has been proposed as a possible candidate for future in-body networks. However, the attenuation of body tissues at gigahertz frequencies could be a serious drawback. Experimental measurements for channel modeling are not easy to carry out, while the use of humans is practically forbidden. Sophisticated simulation tools could provide inaccurate results since they are not able to reproduce all the in-body channel conditions. Chemical solutions known as phantoms could provide a fair approximation of body tissues¿ behavior. In this work, the Time Reversal technique is assessed to increase the channel performance of in-body communications. For this task, a large volume of experimental measurements is performed at the low part of UWB spectrum (3.1-5.1 GHz) by using a highly accurate phantom-based measurement setup. This experimental setup emulates an in-body to in-body scenario, where all the nodes are implanted inside the body. Moreover, the in-body channel characteristics such as the path loss, the correlation in transmission and reception, and the reciprocity of the channel are assessed and discussed.This work was supported by the Programa de Ayudas de Investigacion y Desarrollo (PAID-01-16) from Universitat Politecnica de Valencia and by the Ministerio de Economia y Competitividad, Spain (TEC2014-60258-C2-1-R), by the European FEDER funds.Andreu-Estellés, C.; Garcia-Pardo, C.; Castelló-Palacios, S.; Cardona Marcet, N. (2018). Experimental Assessment of Time Reversal for In-Body to In-Body UWB Communications. Wireless Communications and Mobile Computing (Online). 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Communication channel analysis and real time compressed sensing for high density neural recording devices

Next generation neural recording and Brain- Machine Interface (BMI) devices call for high density or distributed systems with more than 1000 recording sites. As the recording site density grows, the device generates data on the scale of several hundred megabits per second (Mbps). Transmitting such large amounts of data induces significant power consumption and heat dissipation for the implanted electronics. Facing these constraints, efficient on-chip compression techniques become essential to the reduction of implanted systems power consumption. This paper analyzes the communication channel constraints for high density neural recording devices. This paper then quantifies the improvement on communication channel using efficient on-chip compression methods. Finally, This paper describes a Compressed Sensing (CS) based system that can reduce the data rate by > 10x times while using power on the order of a few hundred nW per recording channel

A computational model for real-time calculation of electric field due to transcranial magnetic stimulation in clinics

The aim of this paper is to propose an approach for an accurate and fast (real-time) computation of the electric field induced inside the whole brain volume during a transcranial magnetic stimulation (TMS) procedure. The numerical solution implements the admittance method for a discretized realistic brain model derived from Magnetic Resonance Imaging (MRI). Results are in a good agreement with those obtained using commercial codes and require much less computational time. An integration of the developed codewith neuronavigation toolswill permit real-time evaluation of the stimulated brain regions during the TMSdelivery, thus improving the efficacy of clinical applications

Model estimation of cerebral hemodynamics between blood flow and volume changes: a data-based modeling approach

It is well known that there is a dynamic relationship between cerebral blood flow (CBF) and cerebral blood volume (CBV). With increasing applications of functional MRI, where the blood oxygen-level-dependent signals are recorded, the understanding and accurate modeling of the hemodynamic relationship between CBF and CBV becomes increasingly important. This study presents an empirical and data-based modeling framework for model identification from CBF and CBV experimental data. It is shown that the relationship between the changes in CBF and CBV can be described using a parsimonious autoregressive with exogenous input model structure. It is observed that neither the ordinary least-squares (LS) method nor the classical total least-squares (TLS) method can produce accurate estimates from the original noisy CBF and CBV data. A regularized total least-squares (RTLS) method is thus introduced and extended to solve such an error-in-the-variables problem. Quantitative results show that the RTLS method works very well on the noisy CBF and CBV data. Finally, a combination of RTLS with a filtering method can lead to a parsimonious but very effective model that can characterize the relationship between the changes in CBF and CBV

Improved reception of in-body signals by means of a wearable multi-antenna system

High data-rate wireless communication for in-body human implants is mainly performed in the 402-405 MHz Medical Implant Communication System band and the 2.45 GHz Industrial, Scientific and Medical band. The latter band offers larger bandwidth, enabling high-resolution live video transmission. Although in-body signal attenuation is larger, at least 29 dB more power may be transmitted in this band and the antenna efficiency for compact antennas at 2.45 GHz is also up to 10 times higher. Moreover, at the receive side, one can exploit the large surface provided by a garment by deploying multiple compact highly efficient wearable antennas, capturing the signals transmitted by the implant directly at the body surface, yielding stronger signals and reducing interference. In this paper, we implement a reliable 3.5 Mbps wearable textile multi-antenna system suitable for integration into a jacket worn by a patient, and evaluate its potential to improve the In-to-Out Body wireless link reliability by means of spatial receive diversity in a standardized measurement setup. We derive the optimal distribution and the minimum number of on-body antennas required to ensure signal levels that are large enough for real-time wireless endoscopy-capsule applications, at varying positions and orientations of the implant in the human body