Contact, high-resolution spatial diffuse reflectance imaging system for skin condition diagnosis: a first-in-human clinical trial.

SIGNIFICANCE: Oxygenation is one of the skin tissue physiological properties to follow for patient care management. Furthermore, long-term monitoring of such parameters is needed at the patient bed as well as outside the hospital. Diffuse reflectance spectroscopy has been widely used for this purpose. AIM: The aim of the study is to propose a low-cost system for the long-term measurement of skin physiological parameters in contact. APPROACH: We have developed a low-cost, wearable, CMOS-based device. We propose an original method for processing diffuse reflectance data to calculate the tissue oxygen saturation (StO2). RESULTS: We tested the device for the assessment of tissue oxygenation during a first-in-human clinical trial that took place at the Grenoble University Hospital France. CONCLUSIONS: The results of this clinical trial show a good accordance between our sensor and commercial devices used a reference.

Evaluation in Healthy Subjects of a Transcutaneous Carbon Dioxide Monitoring Wristband during Hypo and Hypercapnia Conditions.

The development of wearable devices for healthcare monitoring is of primary interest, in particular for homecare applications. But it is challenging to develop an evaluation framework to test and optimize such a device by following a non-invasive protocol. As well established reference devices do exist for capnometry, we propose a protocol to evaluate and compare the performance of the transcutaneous carbon dioxide monitoring wristband that we develop. We present here this protocol, the signal processing pipeline and the data analysis based on signal alignment and intercorrelation study, and the first results on a cohort of 13 healthy subjects. This test allows demonstrating the influence of the device response time and of the carbon dioxide content in the ambient air.Clinical Relevance-The protocol described here allows to test and optimize the new device in clinical conditions simulating hypo and hypercapnia variations on a subject at rest, as it would be the case at home to monitor the health status of chronic respiratory patients, and to compare the performances with reference devices. A strong intercorrelation greater than 0.8 has been observed in 5 healthy subjects out of 13 and factors influencing the intercorrelation are suggested.

First Evaluation of a Transcutaneous Carbon Dioxide Monitoring Wristband Device during a Cardiopulmonary Exercise Test.

We introduce an innovative wristband wireless device based on a dual wavelength NDIR optical measurement and an optimized thermo-fluidic channel to improve the extraction of the carbon dioxide gas from the blood within the heated skin region. We describe a signal processing model combining an innovative linear quadratic model of the optical measurement and a fluidic model. The evaluation is achieved using a cardiopulmonary exercise test (CPET). We compare carbon dioxide tension measurement at the forearm level using our device, with an electrochemical measurement at the forearm level, and an optical measurement of the end-tidal exhaled breath. These curves demonstrate a significant reduction of the variability of carbon dioxide pressure measurement with respect to the pressure dynamic range during the test.

Design and development of an impedimetric-based system for the remote monitoring of home-based dialysis patients.

A key clinical challenge is to determine the desired 'dry weight' of a patient in order to terminate the dialysis procedure at the optimal moment and thus avoid the effects of over- and under-hydration. It has been found that the effects of haemodialysis on patients can be conveniently monitored using whole-body bioimpedance measurements. The identified need of assessing the hydrational status of patients undergoing haemodialysis at home gave rise to the present Dialydom (DIALYse à DOMicile) project. The aim of the project is to develop a convenient miniaturised impedance monitoring device for localised measurements (on the calf) in order to estimate an impedimetric hydrational index of the home-based patient, and to transmit this and other parameters to a remote clinical site. Many challenges must be overcome to develop a robust and valid home-based device. Some of these are presented in the paper.

Neural adaptation to responsive stimulation: a comparison of auditory and deep brain stimulation in a rat model of absence epilepsy.

BACKGROUND: Responsive deep brain stimulation (rDBS) has been recently proposed to block epileptic seizures at onset. Yet, long-term stability of brain responses to such kind of stimulation is not known. OBJECTIVE: To quantify the neural adaptation to repeated rDBS as measured by the changes of anti-epileptic efficacy of bilateral DBS of the substantia nigra pars reticulata (SNr) versus auditory stimulation, in a rat model of spontaneous recurrent absence seizures (GAERS). METHODS: Local field potentials (LFP) were recorded in freely moving animals during 1 h up to 24 h under automated responsive stimulations (SNr-DBS and auditory). Comparison of seizure features was used to characterise transient (repetition-suppression effect) and long-lasting (stability of anti-epileptic efficacy, i.e. ratio of successfully interrupted seizures) effects of responsive stimulations. RESULTS: SNr-DBS was more efficient than auditory stimulation in blocking seizures (97% vs. 52% of seizures interrupted, respectively). Sensitivity to minimal interstimulus interval was much stronger for SNr-DBS than for auditory stimulation. Anti-epileptic efficacy of SNr-DBS was remarkably stable during long-term (24 h) recordings. CONCLUSIONS: In the GAERS model, we demonstrated the superiority of SNr-DBS to suppress seizures, as compared to auditory stimulation. Importantly, we found no long-term habituation to rDBS. However, when seizure recurrence was frequent, rDBS lack anti-epileptic efficacy because responsive stimulations became too close (time interval < 40 s) suggesting the existence of a refractory period. This study thus motivates the use of automated rDBS in patients having transient seizures separated by sufficiently long intervals.

Iterative N-way partial least squares for a binary self-paced brain-computer interface in freely moving animals.

In this paper a tensor-based approach is developed for calibration of binary self-paced brain-computer interface (BCI) systems. In order to form the feature tensor, electrocorticograms, recorded during behavioral experiments in freely moving animals (rats), were mapped to the spatial-temporal-frequency space using the continuous wavelet transformation. An N-way partial least squares (NPLS) method is applied for tensor factorization and the prediction of a movement intention depending on neuronal activity. To cope with the huge feature tensor dimension, an iterative NPLS (INPLS) algorithm is proposed. Computational experiments demonstrated the good accuracy and robustness of INPLS. The algorithm does not depend on any prior neurophysiological knowledge and allows fully automatic system calibration and extraction of the BCI-related features. Based on the analysis of time intervals preceding the BCI events, the calibration procedure constructs a predictive model of control. The BCI system was validated by experiments in freely moving animals under conditions close to those in a natural environment.

BioMEA: a versatile high-density 3D microelectrode array system using integrated electronics.

Microelectrode arrays (MEAs) offer a powerful tool to both record activity and deliver electrical microstimulations to neural networks either in vitro or in vivo. Microelectronics microfabrication technologies now allow building high-density MEAs containing several hundreds of microelectrodes. However, dense arrays of 3D micro-needle electrodes, providing closer contact with the neural tissue than planar electrodes, are not achievable using conventional isotropic etching processes. Moreover, increasing the number of electrodes using conventional electronics is difficult to achieve into compact devices addressing all channels independently for simultaneous recording and stimulation. Here, we present a full modular and versatile 256-channel MEA system based on integrated electronics. First, transparent high-density arrays of 3D-shaped microelectrodes were realized by deep reactive ion etching techniques of a silicon substrate reported on glass. This approach allowed achieving high electrode aspect ratios, and different shapes of tip electrodes. Next, we developed a dedicated analog 64-channel Application Specific Integrated Circuit (ASIC) including one amplification stage and one current generator per channel, and analog output multiplexing. A full modular system, called BIOMEA, has been designed, allowing connecting different types of MEAs (64, 128, or 256 electrodes) to different numbers of ASICs for simultaneous recording and/or stimulation on all channels. Finally, this system has been validated experimentally by recording and electrically eliciting low-amplitude spontaneous rhythmic activity (both LFPs and spikes) in the developing mouse CNS. The availability of high-density MEA systems with integrated electronics will offer new possibilities for both in vitro and in vivo studies of large neural networks.