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Stroke rehabilitation is often terminated once a plateau in motor recovery is observed, but new training modalities have demonstrated that further functional improvement is possible after the onset of the chronic phase. learn more In particular, feedback technologies augmenting error proved to foster the relearning process. Here we explore the possibility of a robot-free implementation of Error-Augmentation (EA), where only visual feedback is distorted. We present the interim results from our ongoing blinded, randomized, controlled clinical trial testing the efficacy of parallel bimanual reaching with visual EA. Subjects trained in the virtual environment in 45-minute sessions, three times a week, for three weeks, half with and half without EA. A blinded therapist performed clinical evaluations before, 1 week after, and two months after training. Available results showed that both groups significantly improved. An advantage in the treatment group could be tracked at all time points, but no statistical significance was detectable between groups. Gains in the two groups were found to be compatible with the results of previous studies using robots and may prove to have similar effectiveness without the need for a costly and complicated robotic device. One new finding was that EA caused significantly higher inter-trial variability.Cancer therapies are constantly evolving. Currently, heating tumor tissue is becoming more accessible as a stand-alone method or in combination with other therapies. Due to its multiple advantages over other heating mechanisms, microwave hyperthermia has recently gained a lot of traction. In this work, we present a complementary split-ring resonator that is simultaneously excited in two independent frequency bands. With a high-power signal, the applicator is excited and heats the tissue-under-test up to 50°C with an average heating rate of 0.72°C per second. Furthermore, we present a dielectric temperature control system using the same applicator for microwave hyperthermia applications, which currently still requires an additional thermometry system. By exciting the applicator with a low-power signal, we can constantly monitor its resonant frequency. This resonant frequency depends on the tissue properties, which in turn are temperature-dependent. In the temperature range from 20-50°C, a positive correlation between the temperature and resonant frequency was established.Clinical relevance - Exploiting the dual-band behavior of the complementary split-ring resonator to heat the tissue-under-test while dielectrically monitoring its temperature, creates new possibilities towards a theranostic, non-invasive microwave hyperthermia applicator.Fine motor movement is a demonstrated biomarker for many health conditions that are especially difficult to diagnose early and require sensitivity to change in order to monitor over time. This is particularly relevant for neurodegenerative diseases (NDs), including Parkinson's Disease (PD) and Alzheimer's Disease (AD), which are associated with early changes in handwriting and fine motor skills. Kinematic analysis of handwriting is an emerging method for assessing fine motor movement ability, with data typically collected by digitizing tablets; however, these are often expensive, unfamiliar to patients, and are limited in the scope of collectible data. In this paper, we present a vision-based system for the capture and analysis of handwriting kinematics using a commodity camera and RGB video. We achieve writing position estimation within 0.5 mm and speed and acceleration errors of less than 1.1%. We further demonstrate that this data collection process can be part of an ND screening system with a developed en as an accessible form of disease long-term monitoring through telemedicine.The major reason for preventable hospital death is venous thromboembolism (VTE). Non-pharmacological treatment options include electrical stimulation or compression therapy to improve blood flow in the extremities. Textile electrodes offer potential to replace bulky devices commonly used in this field, thereby improving the user compliance. In this work, the performance of dry and wet knitted electrodes in combination with pressure application to the electrode was evaluated in neuromuscular electrical stimulation (NMES). A motor point stimulation on the calf was performed on nine healthy subjects to induce a plantarflexion and the required stimulation intensity as well as the perceived pain were assessed. The performance of the different electrode constructions was compared and the influence of the pressure application was analysed. The results show that wet textile electrodes (0.9 % saline solution) perform significantly better than dry electrodes. However, opportunities were found for improving the performance of dry textile electrodes by using an uneven surface topography in combination with an intermediate to high pressure application to the electrode (> 20 mmHg), e.g. by using a compression stocking. Moreover, the smaller of the two tested electrode areas (16 cm2; 32 cm2) appears to be favourable in terms of stimulation comfort and efficiency.Transcranial Magnetic Stimulation (TMS) is a non-invasive method for safe and painless activation of cortical neurons. On-line visualization of the induced Electric field (E-field) has the potential to improve quantitative targeting and dosing of stimulation, however present commercially available systems are limited by simplified approximations of the anatomy. Here, we developed a near real-time method to accurately approximate the induced E-field of a freely moving TMS coil with an individualized high-resolution head model. We use a set of magnetic dipoles around the head to approximate the total E-field of a moving TMS coil. First, we match the incident field of the dipole basis set with the incident E-field of the moving coil. Then, based on the principle of superposition and uniqueness of the solutions, we apply same basis coefficients to the total E-field of the basis set. The computed E-fields results show high similarity with an established TMS solver both in terms of the amplitude and the spatial distribution patterns. The proposed method enables rapid visualization of the E-field with ~100 ms of computation time enabling interactive planning, targeting, dosing and coil positioning tasks for TMS neuronavigation.Peripheral oxygen saturation (SpO2) plays a key role in diagnosing sleep apnea. It is mainly measured via transmission pulse oximetry at the fingertip, an approach less suited for long-term monitoring over several nights.In this study we tested a more patient-friendly solution via a reflectance pulse oximetry device. Having previously observed issues with pulse oximetry at the wrist, we investigated in this study the influence of the location of our device (upper arm vs. wrist) to measure SpO2. Accuracy was compared against state-of-the-art fingertip SpO2 measurements during a full overnight polysomnography in nine patients with suspected sleep apnea.The upper arm location clearly showed a lower root mean square error ARMS = 1.8% than the wrist ARMS = 2.5% and a lower rate of automatic data rejection (19% vs 25%). Irrespective of the measurement location the accuracies obtained comply with the ISO standard and the FDA guidance for pulse oximeters. In contrast to the wrist, the upper arm location seemed to be more resilient to deteriorating influences such as venous blood.Reflectance pulse oximetry at the wrist remains challenging but the upper arm could provide remedy for more robust SpO2 estimates to reliably screen for sleep apnea and other diseases.Clinical Relevance- The performance of reflectance pulse oximetry measured at the upper arm during sleep is superior to measurements at the wrist which are perturbed by undesired large fluctuations suspected to be caused by venous blood. If confirmed, this could also apply to the optical measurement of other vital signs such as blood pressure.Traumatic brain injury (TBI) is one of the leading causes of death worldwide, yet there is no systematic approach to monitor TBI non-invasively. The main motivation of this work is to create new knowledge relating to light brain interaction using a Monte Carlo Model, which could aid in the development of non-invasive optical sensors for the continuous assessment of TBI. To this aim, a multilayer model tissue-model of adult human head was developed and explored at the near-infrared optical wavelength. Investigation reveals that maximum light (40-50%) is absorbed in the skull and the minimum light is absorbed in the subarachnoid space (0-1%). It was found that the absorbance of light decreases with increasing source-detector separation up to 3cm where light travels through the subarachnoid space, after which the absorbance increases with the increasing separation. Such information will be helpful towards the modelling of neurocritical brain tissue followed by the sensor development.Poor understanding of brain recovery after injury, sparsity of evaluations and limited availability of healthcare services hinders the success of neurorehabilitation programs in rural communities. The availability of neuroimaging ca-pacities in remote communities can alleviate this scenario supporting neurorehabilitation programs in remote settings. This research aims at building a multimodal EEG-fNIRS neuroimaging platform deployable to rural communities to support neurorehabilitation efforts. A Raspberry Pi 4 is chosen as the CPU for the platform responsible for presenting the neurorehabilitation stimuli, acquiring, processing and storing concurrent neuroimaging records as well as the proper synchronization between the neuroimaging streams. We present here two experiments to assess the feasibility and characterization of the Raspberry Pi as the core for a multimodal EEG-fNIRS neuroimaging platform; one over controlled conditions using a combination of synthetic and real data, and another from a full test during resting state. CPU usage, RAM usage and operation temperature were measured during the tests with mean operational records below 40% for CPU cores, 13.6% for memory and 58.85 ° C for temperatures. Package loss was inexistent on synthetic data and negligible on experimental data. Current consumption can be satisfied with a 1000 mAh 5V battery. The Raspberry Pi 4 was able to cope with the required workload in conditions of operation similar to those needed to support a neurorehabilitation evaluation.In this work, we demonstrate an adjustable microfluidic tactile sensor for measurement of post-exercise response of local arterial parameters. The sensor entailed a polydimethylsiloxane (PDMS) microstructure embedded with a 5×1 resistive transducer array. The pulse signal in an artery deflected the microstructure and registered as a resistance change by the transducer aligned at the artery. PDMS layers of different thicknesses were added to adjust the microstructure thickness for achieving good sensor-artery conformity at the radial artery (RA) and the carotid artery (CA). Pulse signals of nine (n=9) young healthy male subjects were measured at-rest and at different times post-exercise, and a medical instrument was used to simultaneously measure their blood pressure and heart rate. Vibration-model-based analysis was conducted on a measured pulse signal to estimate local arterial parameters elasticity, viscosity, and radius. The arterial elasticity and viscosity increased, and the arterial radius decreased at the two arteries 1min post-exercise, relative to at-rest.
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