PhysioKit: An Open-Source, Low-Cost Physiological Computing Toolkit for Single- and Multi-User Studies.

The proliferation of physiological sensors opens new opportunities to explore interactions, conduct experiments and evaluate the user experience with continuous monitoring of bodily functions. Commercial devices, however, can be costly or limit access to raw waveform data, while low-cost sensors are efforts-intensive to setup. To address these challenges, we introduce PhysioKit, an open-source, low-cost physiological computing toolkit. PhysioKit provides a one-stop pipeline consisting of (i) a sensing and data acquisition layer that can be configured in a modular manner per research needs, and (ii) a software application layer that enables data acquisition, real-time visualization and machine learning (ML)-enabled signal quality assessment. This also supports basic visual biofeedback configurations and synchronized acquisition for co-located or remote multi-user settings. In a validation study with 16 participants, PhysioKit shows strong agreement with research-grade sensors on measuring heart rate and heart rate variability metrics data. Furthermore, we report usability survey results from 10 small-project teams (44 individual members in total) who used PhysioKit for 4-6 weeks, providing insights into its use cases and research benefits. Lastly, we discuss the extensibility and potential impact of the toolkit on the research community.

Relationship between Loudness Dependence of Auditory-evoked Potentials and Suicidality.

Objective: : Serotonin concentration is associated with suicide in patients with major depressive disorder. Loudness dependence of auditory-evoked potentials (LDAEPs), a representative neurophysiological indicator, is related to serotonin activity. Therefore, this study aimed to investigate the relationship between LDAEPs and suicidal ideation, suicide attempts, and the severity of depression. Methods: : We evaluated the scalp N1, P2, and N1/P2 LDAEPs along with standardized low-resolution brain electromagnetic tomography (sLORETA)-localized N1, P2, and N1/P2 LDAEPs of 221 patients with major depressive disorder. The demographic and clinical data of the patients, including data on suicidal ideation and previous suicide attempts, were obtained from clinical interviews and medical records. The severity of depression was assessed using the Beck Depression Inventory and Hamilton Depression Rating Scale, whereas suicidal ideation was evaluated using the Beck Scale for Suicidal Ideation (BSS). Results: : The total BSS score was associated with low N1/P2 LDAEP (p = 0.045), whereas P2 sLORETA-LDAEP was associated with lower previous suicide attempts (p = 0.043). In addition, suicide attempt was correlated with an elevated P2 left sLORETA-LDAEP (coefficient = 4.638, p = 0.038). Conclusion: : These findings suggest that suicidal ideation is associated with decreased LDAEP, whereas suicide attempt is associated with increased LDAEP.

Three-Dimensional Touch Device with Two Terminals.

A crossbar array is an essential element that determines the operating position and simplifies the structure of devices. However, in the crossbar array, wiring numerous electrodes to address many positions poses significant challenges. In this study, a method is proposed that utilizes only two electrodes to determine multiple positions. The method significantly simplifies the wiring and device fabrication process. Instead of defining the node location of the crossbar, it is experimentally demonstrated that the x-y-z coordinates can be determined from i) the resistance change as a function of distance, ii) the resistance variation influenced by the electrode composition, and iii) capacitance fluctuation resulting from changes in the dielectric thickness. By employing two-terminal transparent electrodes, a fully functional 3D touch device is successfully fabricated, introducing a groundbreaking approach to simplify input device architectures.

Hybrid Bionic Nerve Interface for Application in Bionic Limbs.

Intuitive and perceptual neuroprosthetic systems require a high degree of neural control and a variety of sensory feedback, but reliable neural interfaces for long-term use that maintain their functionality are limited. Here, a novel hybrid bionic interface is presented, fabricated by integrating a biological interface (regenerative peripheral nerve interface (RPNI)) and a peripheral neural interface to enhance the neural interface performance between a nerve and bionic limbs. This interface utilizes a shape memory polymer buckle that can be easily implanted on a severed nerve and make contact with both the nerve and the muscle graft after RPNI formation. It is demonstrated that this interface can simultaneously record different signal information via the RPNI and the nerve, as well as stimulate them separately, inducing different responses. Furthermore, it is shown that this interface can record naturally evoked signals from a walking rabbit and use them to control a robotic leg. The long-term functionality and biocompatibility of this interface in rabbits are evaluated for up to 29 weeks, confirming its promising potential for enhancing prosthetic control.

Implantable Electroceutical Approach Improves Myelination by Restoring Membrane Integrity in a Mouse Model of Peripheral Demyelinating Neuropathy.

Although many efforts are undertaken to treat peripheral demyelinating neuropathies based on biochemical interventions, unfortunately, there is no approved treatment yet. Furthermore, previous studies have not shown improvement of the myelin membrane at the biomolecular level. Here, an electroceutical treatment is introduced as a biophysical intervention to treat Charcot-Marie-Tooth (CMT) disease-the most prevalent peripheral demyelinating neuropathy worldwide-using a mouse model. The specific electrical stimulation (ES) condition (50 mV mm-1 , 20 Hz, 1 h) for optimal myelination is found via an in vitro ES screening system, and its promyelinating effect is validated with ex vivo dorsal root ganglion model. Biomolecular investigation via time-of-flight secondary ion mass spectrometry shows that ES ameliorates distribution abnormalities of peripheral myelin protein 22 and cholesterol in the myelin membrane, revealing the restoration of myelin membrane integrity. ES intervention in vivo via flexible implantable electrodes shows not only gradual rehabilitation of mouse behavioral phenotypes (balance and endurance), but also restored myelin thickness, compactness, and membrane integrity. This study demonstrates, for the first time, that an electroceutical approach with the optimal ES condition has the potential to treat CMT disease and restore impaired myelin membrane integrity, shifting the paradigm toward practical interventions for peripheral demyelinating neuropathies.

Advanced Neural Interface toward Bioelectronic Medicine Enabled by Micro-Patterned Shape Memory Polymer.

Recently, methods for the treatment of chronic diseases and disorders through the modulation of peripheral and autonomic nerves have been proposed. To investigate various treatment methods and results, experiments are being conducted on animals such as rabbits and rat. However the diameter of the targeted nerves is small (several hundred µm) and it is difficult to modulate small nerves. Therefore, a neural interface that is stable, easy to implant into small nerves, and is biocompatible is required. Here, to develop an advanced neural interface, a thiol-ene/acrylate-based shape memory polymer (SMP) was fabricated with a double clip design. This micro-patterned design is able to be implanted on a small branch of the sciatic nerve, as well as the parasympathetic pelvic nerve, using the shape memory effect (SME) near body temperature. Additionally, the IrO2 coated neural interface was implanted on the common peroneal nerve in order to perform electrical stimulation and electroneurography (ENG) recording. The results demonstrate that the proposed neural interface can be used for the modulation of the peripheral nerve, including the autonomic nerve, towards bioelectronic medicine.

Silicon Oxide Etching Process of NF3 and F3NO Plasmas with a Residual Gas Analyzer.

The use of NF3 is significantly increasing every year. However, NF3 is a greenhouse gas with a very high global warming potential. Therefore, the development of a material to replace NF3 is required. F3NO is considered a potential replacement to NF3. In this study, the characteristics and cleaning performance of the F3NO plasma to replace the greenhouse gas NF3 were examined. Etching of SiO2 thin films was performed, the DC offset of the plasma of both gases (i.e., NF3 and F3NO) was analyzed, and a residual gas analysis was performed. Based on the analysis results, the characteristics of the F3NO plasma were studied, and the SiO2 etch rates of the NF3 and F3NO plasmas were compared. The results show that the etch rates of the two gases have a difference of 95% on average, and therefore, the cleaning performance of the F3NO plasma was demonstrated, and the potential benefit of replacing NF3 with F3NO was confirmed.

Recent progress on peripheral neural interface technology towards bioelectronic medicine.

Modulation of the peripheral nervous system (PNS) has a great potential for therapeutic intervention as well as restore bodily functions. Recent interest has focused on autonomic nerves, as they regulate extensive functions implicated in organ physiology, chronic disease state and appear tractable to targeted modulation of discrete nerve units. Therapeutic interventions based on specific bioelectronic neuromodulation depend on reliable neural interface to stimulate and record autonomic nerves. Furthermore, the function of stimulation and recording requires energy which should be delivered to the interface. Due to the physiological and anatomical challenges of autonomic nerves, various forms of this active neural interface need to be developed to achieve next generation of neural interface for bioelectronic medicine. In this article, we present an overview of the state-of-the-art for peripheral neural interface technology in relation to autonomic nerves. Also, we reveal the current status of wireless neural interface for peripheral nerve applications. Recent studies of a novel concept of self-sustainable neural interface without battery and electronic components are presented. Finally, the recent results of non-invasive stimulation such as ultrasound and magnetic stimulation are covered and the perspective of the future research direction is provided.

Breathing Biofeedback Relaxation Intervention for Wheelchair Users in City Navigation.

Manual wheelchair users experience numerous invisible barriers while navigating cities, often reporting how stressful journeys are. This stress affects a wheelchair user's quality of life. To alleviate such psychological burden, we propose a novel intervention strategy with a respiratory biofeedback interface which is designed to help users feel relaxed in urban navigation. We conducted a study in a real-world setting to explore its potential to provide real-time psychological support. From qualitative and quantitative analysis, we report on the strengths and weaknesses of the approach.

Instant Stress: Detection of Perceived Mental Stress Through Smartphone Photoplethysmography and Thermal Imaging.

BACKGROUND: A smartphone is a promising tool for daily cardiovascular measurement and mental stress monitoring. A smartphone camera-based photoplethysmography (PPG) and a low-cost thermal camera can be used to create cheap, convenient, and mobile monitoring systems. However, to ensure reliable monitoring results, a person must remain still for several minutes while a measurement is being taken. This is cumbersome and makes its use in real-life situations impractical. OBJECTIVE: We proposed a system that combines PPG and thermography with the aim of improving cardiovascular signal quality and detecting stress responses quickly. METHODS: Using a smartphone camera with a low-cost thermal camera added on, we built a novel system that continuously and reliably measures 2 different types of cardiovascular events: (1) blood volume pulse and (2) vasoconstriction/dilation-induced temperature changes of the nose tip. 17 participants, involved in stress-inducing mental workload tasks, measured their physiological responses to stressors over a short time period (20 seconds) immediately after each task. Participants reported their perceived stress levels on a 10-cm visual analog scale. For the instant stress inference task, we built novel low-level feature sets representing cardiovascular variability. We then used the automatic feature learning capability of artificial neural networks to improve the mapping between the extracted features and the self-reported ratings. We compared our proposed method with existing hand-engineered features-based machine learning methods. RESULTS: First, we found that the measured PPG signals presented high quality cardiac cyclic information (mean pSQI: 0.755; SD 0.068). We also found that the measured thermal changes of the nose tip presented high-quality breathing cyclic information and filtering helped extract vasoconstriction/dilation-induced patterns with fewer respiratory effects (mean pSQI: from 0.714 to 0.157). Second, we found low correlations between the self-reported stress scores and the existing metrics of the cardiovascular signals (ie, heart rate variability and thermal directionality) from short measurements, suggesting they were not very dependent upon one another. Third, we tested the performance of the instant perceived stress inference method. The proposed method achieved significantly higher accuracies than existing precrafted features-based methods. In addition, the 17-fold leave-one-subject-out cross-validation results showed that combining both modalities produced higher accuracy than using PPG or thermal imaging only (PPG+Thermal: 78.33%; PPG: 68.53%; Thermal: 58.82%). The multimodal results are comparable to the state-of-the-art stress recognition methods that require long-term measurements. Finally, we explored effects of different data labeling strategies on the sensitivity of our inference methods. Our results showed the need for separation of and normalization between individual data. CONCLUSIONS: The results demonstrate the feasibility of using smartphone-based imaging for instant stress detection. Given that this approach does not need long-term measurements requiring attention and reduced mobility, we believe it is more suitable for mobile mental health care solutions in the wild.

Robust magnon-photon coupling in a planar-geometry hybrid of inverted split-ring resonator and YIG film.

We experimentally demonstrate strongly enhanced coupling between excited magnons in an Yttrium Iron Garnet (YIG) film and microwave photons in an inverted pattern of split-ring resonator (noted as ISRR). The anti-crossing effects of the ISRR's photon mode and the YIG's magnon modes were found from |S21|-versus-frequency measurements for different strengths and directions of externally applied magnetic fields. The spin-number-normalized coupling strength (i.e. single spin-photon coupling) [Formula: see text] was determined to 0.194 Hz ([Formula: see text] = 90 MHz) at 3.7 GHz frequency. Furthermore, we found that additional fine features in the anti-crossing region originate from the excitation of different spin-wave modes (such as the magnetostatic surface and the backward-volume magnetostatic spin-waves) rather than the Kittel-type mode. These spin-wave modes, as coupled with the ISRR mode, modify the anti-crossing effect as well as their coupling strength. An equivalent circuit model very accurately reproduced the observed anti-crossing effect and its coupling strength variation with the magnetic field direction in the planar-geometry ISRR/YIG hybrid system. This work paves the way for the design of new types of high-gain magnon-photon coupling systems in planar geometry.

Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging.

The ability to monitor the respiratory rate, one of the vital signs, is extremely important for the medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to undertake everyday activities, are required. However, current monitoring systems can be obtrusive, requiring users to wear respiration belts or nasal probes. Alternatively, contactless digital image sensor based remote-photoplethysmography (PPG) can be used. However, remote PPG requires an ambient source of light, and does not work properly in dark places or under varying lighting conditions. Recent advances in thermographic systems have shrunk their size, weight and cost, to the point where it is possible to create smart-phone based respiration rate monitoring devices that are not affected by lighting conditions. However, mobile thermal imaging is challenged in scenes with high thermal dynamic ranges (e.g. due to the different environmental temperature distributions indoors and outdoors). This challenge is further amplified by general problems such as motion artifacts and low spatial resolution, leading to unreliable breathing signals. In this paper, we propose a novel and robust approach for respiration tracking which compensates for the negative effects of variations in the ambient temperature and motion artifacts and can accurately extract breathing rates in highly dynamic thermal scenes. The approach is based on tracking the nostril of the user and using local temperature variations to infer inhalation and exhalation cycles. It has three main contributions. The first is a novel Optimal Quantization technique which adaptively constructs a color mapping of absolute temperature to improve segmentation, classification and tracking. The second is the Thermal Gradient Flow method that computes thermal gradient magnitude maps to enhance the accuracy of the nostril region tracking. Finally, we introduce the Thermal Voxel method to increase the reliability of the captured respiration signals compared to the traditional averaging method. We demonstrate the extreme robustness of our system to track the nostril-region and measure the respiratory rate by evaluating it during controlled respiration exercises in high thermal dynamic scenes (e.g. strong correlation (r = 0.9987) with the ground truth from the respiration-belt sensor). We also demonstrate how our algorithm outperformed standard algorithms in settings with different amounts of environmental thermal changes and human motion. We open the tracked ROI sequences of the datasets collected for these studies (i.e. under both controlled and unconstrained real-world settings) to the community to foster work in this area.

Coupled gyration modes in one-dimensional skyrmion arrays in thin-film nanostrips as new type of information carrier.

We report on a micromagnetic numerical simulation study of dynamic coupling between neighboring skyrmions periodically arranged in narrow-width nanostrips. We explored the coupled gyration modes and their characteristic dispersions in terms of the interdistance between the neighboring skyrmions. The application of perpendicular magnetic fields allows for the control and modification of the dispersion of the coupled gyration modes. The coupled gyration modes of individual skyrmions might provide a new type of information carrier in narrow-width straight and curved nanostrips, as driven by magnetic interactions in such continuous thin films.

Peritoneal-mediastinal leakage complication of peritoneal dialysis.

The authors report a case of mediastinal fluid collection resulting from peritoneal-mediastinal communication after continuous ambulatory peritoneal dialysis (CAPD). To the best of the authors' knowledge, this is the first reported case in the medical literature. A dry cough developed in the patient who had been receiving CAPD for 4 years. A mediastinal mass owing to peritoneal leakage of dialysate to the mediastinum was confirmed by a computed tomography scan taken 4 hours after the intraperitoneal infusion of contrast-mixed dialysate. The leakage persisted for 12 weeks after the discontinuation of CAPD fluid instillation.