Multichannel Electrode Research Articles

A Multi-Channel Urine Sensing Detection System Based on Creatinine, Uric Acid, and pH.

Urine analysis represents a crucial diagnostic technique employed in clinical laboratories. Creatinine and uric acid in urine are essential biomarkers in the human body and are widely utilized in clinical analysis. Research has demonstrated a correlation between the normal physiological concentrations of creatinine and uric acid in urine and an increased risk of hypertension, cardiovascular diseases, and kidney disease. Furthermore, the pH of urine indicates the body's metabolic processes and homeostatic balance. In this study, an integrated multi-channel electrochemical sensing system was developed, combining electrochemical analysis techniques, microelectronic design, and nanomaterials. The architecture of an intelligent medical detection system and the production of an interactive interface for smartphones were accomplished. Initially, multi-channel selective electrodes were designed for creatinine, uric acid, and pH detection. The detection range was 10 nM to 100 μM for creatinine, 100 μM to 500 μM for uric acid, and 4 to 9 for pH. Furthermore, interference experiments were also conducted to verify the specificity of the sensors. Subsequently, multi-channel double-sided sensing electrodes and function-integrated hardware were designed, with the standard equations of target analytes stored in the system's read-only memory. Moreover, a WeChat mini-program platform was developed for smartphone interaction, enabling off-body detection and real-time display of target analytes through smartphones. Finally, the aforementioned electrochemical detection electrodes were integrated with the smart sensing system and wirelessly interfaced with smartphones, allowing for intelligent real-time detection in primary healthcare and individual household settings.

Flexible Neural Interface From Non‐Transient Silk Fibroin With Outstanding Conformality, Biocompatibility, and Bioelectric Conductivity

AbstractSilk fibroin (SF) with good biocompatibility can enable an efficient and safe implementation of neural interfaces. However, it has been difficult to achieve a robust integration of patterned conducting materials (multichannel electrodes) on flexible SF film substrates due to the absence of some enduring interactions. In this study, a thermo‐assisted pattern‐transfer technique is demonstrated that can facilely transfer a layer of pre‐set poly(3,4‐ethylenedioxythiophene) (PEDOT) onto the flexible SF substrate through an interpenetrating network of 2 polymer chains, achieving a desired substrate/conductor intertwined interface with good flexibility (≈33 MPa), conductivity (386 S cm−1) and stability in liquid state over 4 months simultaneously. Importantly, this technique can be combined with ink‐jet printing to prepare a multichannel SF‐based neural interface for the electrocorticogram (ECoG) recording and inflammation remission in rat models. The SF‐based neural interface with satisfied tissue conformability, biocompatibility, and bioelectric conductivity is a promising ECoG acquisition tool, where the demonstrated approach can also be useful to develop other SF‐based flexible bioelectronics.

Wireless Spinal Cord Stimulator with Bipolar Multi-Channel Electrode Array

Wireless Spinal Cord Stimulator with Bipolar Multi-Channel Electrode Array

Robust gesture recognition based on attention-deep fast convolutional neural network and surface electromyographic signals.

The surface electromyographic (sEMG) signals reflect human motor intention and can be utilized for human-machine interfaces (HMI). Comparing to the sparse multi-channel (SMC) electrodes, the high-density (HD) electrodes have a large number of electrodes and compact space between electrodes, which can achieve more sEMG information and have the potential to achieve higher performance in myocontrol. However, when the HD electrodes grid shift or damage, it will affect gesture recognition and reduce recognition accuracy. To minimize the impact resulting from the electrodes shift and damage, we proposed an attention deep fast convolutional neural network (attention-DFCNN) model by utilizing the temporary and spatial characteristics of high-density surface electromyography (HD-sEMG) signals. Contrary to the previous methods, which are mostly base on sEMG temporal features, the attention-DFCNN model can improve the robustness and stability by combining the spatial and temporary features. The performance of the proposed model was compared with other classical method and deep learning methods. We used the dataset provided by The University Medical Center Göttingen. Seven able-bodied subjects and one amputee involved in this work. Each subject executed nine gestures under the electrodes shift (10 mm) and damage (6 channels). As for the electrodes shift 10 mm in four directions (inwards; onwards; upwards; downwards) on seven able-bodied subjects, without any pre-training, the average accuracy of attention-DFCNN (0.942 0.04) is significantly higher than LSDA (0.910 0.04, p < 0.01), CNN (0.920 0.05, p < 0.01), TCN (0.840 0.07, p < 0.01), LSTM (0.864 0.08, p < 0.01), attention-BiLSTM (0.852 0.07, p < 0.01), Transformer (0.903 0.07, p < 0.01) and Swin-Transformer (0.908 0.09, p < 0.01). The proposed attention-DFCNN algorithm and the way of combining the spatial and temporary features of sEMG signals can significantly improve the recognition rate when the HD electrodes grid shift or damage during wear.

Neural Circuit Mechanisms of Sinisan formula for the Treatment of adolescent Depression: prefrontal cortex to dorsal raphe nucleus

Ethnopharmacological relevanceSinisan formula (SNSF), documented in the classic books Shanghan Lun, is known for its ability to regulate liver-qi and treat depression. However, its underlying mechanism, particularly its effects on dynamic real-time neuron activity and circuits remains to be fully elucidated. Aim of the studyThis study aimed to investigate the antidepressant effect of SNSF and its central nervous system mechanism on depression-like behaviors, focusing on the prefrontal cortex (PFC) to dorsal raphe nucleus (DRN) neural circuit in a stress-induced adolescent animal model. Materials and methodsSNSF comprised four herbs, the root of Bupleurum chinense DC., the root of Paeonia lactiflora Pall., the fruit of Citrus aurantium L., the rhizome of Glycyrrhiza uralensis Fisch., in equal propotions. The adolescent depression animal model was induced by maternal separation (MS) and chronic restraint stress (CRS). In-vivo multichannel physiological electrodes were implanted into the PFC on PND 28 and animals were recorded 5 times during PND 35–46. From PND 47, the behavioral tests were performed to evaluate the antidepressant efficacy of SNSF. Subsequently, brain tissue was collected for Western blot and immunofluorescence staining analysis. Retro virus was injected into the DRN to explore sources of projections received by serotonergic (5-HTergic) neurons. And the PFC-to-DRN circuit was activated or inhibited through chemogenetic techniques to investigate the effects of SNSF on depression-like behaviors. ResultsAdministration of SNSF for 18 days effectively alleviated depression-like behaviors in MS&CRS adolescent mice. The PFC emerged as the primary glutamatergic projection source of the DRN5−HT neurons. Following SNSF administration for 13/15/18 days, there was an increase in the firing rate of excitatory neurons and excitatory/inhibitory (E/I) ratio in the PFC. MS&CRS stress let to a reduction in the density of 5-HT+ and CaMKII + neurons in the DRN, accompanied by an increase in the density of GAD + neurons in the DRN, while SNSF administration reversed the alterations. Chemogenetic activation of the PFC-to-DRN circuit rescued the depression-like behaviors induced by MS&CRS, whereas suppression of this circuit attenuated the antidepressant effect of SNSF. ConclusionsSNSF significantly mitigated depression-like behaviors in MS&CRS mice. SNSF exerts its antidepressant effects by increasing the E/I ratio in the PFC and enhancing glutamatergic projections from the PFC to the DRN.

Restoration of coherent reach-grasp-pull movement via sequential intraneural peripheral nerve stimulation in rats

Objective. Peripheral nerve stimulation (PNS) has been demonstrated as an effective way to selectively activate muscles and to produce fine hand movements. However, sequential multi-joint upper limb movements, which are critical for paralysis rehabilitation, has not been tested with PNS. Here, we aimed to restore multiple upper limb joint movements through an intraneural interface with a single electrode, achieving coherent reach-grasp-pull movement tasks through sequential stimulation. Approach. A transverse intrafascicular multichannel electrode was implanted under the axilla of the rat’s upper limb, traversing the musculocutaneous, radial, median, and ulnar nerves. Intramuscular electrodes were implanted into the biceps brachii (BB), triceps brachii (TB), flexor carpi radialis (FCR), and extensor carpi radialis (ECR) muscles to record electromyographic (EMG) activity and video recordings were used to capture the kinematics of elbow, wrist, and digit joints. Charge-balanced biphasic pulses were applied to different channels to recruit distinct upper limb muscles, with concurrent recording of EMG signals and joint kinematics to assess the efficacy of the stimulation. Finally, a sequential stimulation protocol was employed by generating coordinated pulses in different channels. Main results. BB, TB, FCR and ECR muscles were selectively activated and various upper limb movements, including elbow flexion, elbow extension, wrist flexion, wrist extension, digit flexion, and digit extension, were reliably generated. The modulation effects of stimulation parameters, including pulse width, amplitude, and frequency, on induced joint movements were investigated and reach-grasp-pull movement was elicited by sequential stimulation. Significance. Our results demonstrated the feasibility of sequential intraneural stimulation for functional multi-joint movement restoration, providing a new approach for clinical rehabilitation in paralyzed patients.

Enhancing multi-channel electrode structures in ceramic fuel cells: Influence of channel geometry on mass transport and electrochemical performance

Solid oxide fuel cell (SOFC) is a promising electrochemical power generation technology that contributes to the decarbonization of the energy field. The electrode-supported design enables the use of thinner electrolytes, but inevitably brings additional gas diffusion resistance, which in turn leads to higher anodic concentration polarization. Therefore, additional structural design of the electrodes is necessary to ensure efficient operation and mass transport resistance minimization. In this study, anode-supported micro-tubular SOFCs with different multi-channel geometries have been attempted, during which samples with 4 channels exhibit unique elliptical structure due to meticulous manipulation. In addition, the 4-channel samples have been compared to the single-channel and 7-channel counterparts, exploring the influential mechanism of the anode micro-structure on gas transfer and electrochemical performances. The study found that the 4-channel cell has the best geometric controllability, with its minimum gas diffusion path reduced to below 50 μm, such thin electrochemical active region (EAR) accounts for >50 % of the entire external surface. Efficient utilization of the geometric surface area considerably facilitates the fuel transport to reach anode/electrolyte interface. By enhancing the mass transport efficiency, the maximum power density of the 4-channel cell reached 1.40 W cm−2 (750 °C), which is 22.8 % and 102.9 % higher than that of the 7-channel and single-channel cells under the same conditions. The highly efficient anode design additionally exhibited exceptional structural integrity and mechanical robustness, thereby ensuring the steady operation of the cell.

GC-STCL: A Granger Causality-Based Spatial-Temporal Contrastive Learning Framework for EEG Emotion Recognition.

EEG signals capture information through multi-channel electrodes and hold promising prospects for human emotion recognition. However, the presence of high levels of noise and the diverse nature of EEG signals pose significant challenges, leading to potential overfitting issues that further complicate the extraction of meaningful information. To address this issue, we propose a Granger causal-based spatial-temporal contrastive learning framework, which significantly enhances the ability to capture EEG signal information by modeling rich spatial-temporal relationships. Specifically, in the spatial dimension, we employ a sampling strategy to select positive sample pairs from individuals watching the same video. Subsequently, a Granger causality test is utilized to enhance graph data and construct potential causality for each channel. Finally, a residual graph convolutional neural network is employed to extract features from EEG signals and compute spatial contrast loss. In the temporal dimension, we first apply a frequency domain noise reduction module for data enhancement on each time series. Then, we introduce the Granger-Former model to capture time domain representation and calculate the time contrast loss. We conduct extensive experiments on two publicly available sentiment recognition datasets (DEAP and SEED), achieving 1.65% improvement of the DEAP dataset and 1.55% improvement of the SEED dataset compared to state-of-the-art unsupervised models. Our method outperforms benchmark methods in terms of prediction accuracy as well as interpretability.

A 16-channel Si probe monolithically integrated with CMOS chips for neural recording

Multi-channel neural electrodes as a crucial means are of great significance for information exchange between the brain and computers. Herein, we present a 16-channel Si-based active neural probe system that achieves a monolithic integration between the electrodes and circuits in a single probe, making it a standalone integrated electrophysiology recording system. The ASIC prepared on a base (2×2mm2) is a 16-channel analog frontend (AFE) for neural recording, and each channel has a low-noise amplifier (LNA), a bandpass filter (BPF), a buffer and a current bias circuit. The 258 neural signal recording electrodes (22×24μm2) are densely packed on a 50 μm thick, 100 μm wide, and 3 mm long shank. The ASIC of neural probe, internal interconnecting wires are all implemented in commercial SMIC 0.18 μm CMOS technology. The neural probe system achieves a 3.6 μVrms input-referred noise (IRN) in a bandwidth of 1.1Hz-10 kHz, 70.8 μW power consumption, 0.0785 mm2 area per channel, as well as an AFE gain of 58.1 dB Furthermore, the impedances of the Au electrodes can be obtained as 0.5–2.1 MΩ at a frequency of 1 kHz. The functionality of a 16-channel silicon-based neural probe is validated in an in-vivo experiment on lab rats.

Multichannel microneedle dry electrode patches for minimally invasive transdermal recording of electrophysiological signals

The collection of multiple-channel electrophysiological signals enables a comprehensive understanding of the spatial distribution and temporal features of electrophysiological activities. This approach can help to distinguish the traits and patterns of different ailments to enhance diagnostic accuracy. Microneedle array electrodes, which can penetrate skin without pain, can lessen the impedance between the electrodes and skin; however, current microneedle methods are limited to single channels and cannot achieve multichannel collection in small areas. Here, a multichannel (32 channels) microneedle dry electrode patch device was developed via a dimensionality reduction fabrication and integration approach and supported by a self-developed circuit system to record weak electrophysiological signals, including electroencephalography (EEG), electrocardiogram (ECG), and electromyography (EMG) signals. The microneedles reduced the electrode–skin contact impedance by penetrating the nonconducting stratum corneum in a painless way. The multichannel microneedle array (MMA) enabled painless transdermal recording of multichannel electrophysiological signals from the subcutaneous space, with high temporal and spatial resolution, reaching the level of a single microneedle in terms of signal precision. The MMA demonstrated the detection of the spatial distribution of ECG, EMG and EEG signals in live rabbit models, and the microneedle electrode (MNE) achieved better signal quality in the transcutaneous detection of EEG signals than did the conventional flat dry electrode array. This work offers a promising opportunity to develop advanced tools for neural interface technology and electrophysiological recording.

Injectable 2D Material-Based Sensor Array for Minimally Invasive Neural Implants.

Intracranial implants for diagnosis and treatment of brain diseases have been developed over the past few decades. However, the platform of conventional implantable devices still relies on invasive probes and bulky sensors in conjunction with large-area craniotomy and provides only limited biometric information. Here, an implantable multi-modal sensor array that can be injected through a small hole in the skull and inherently spread out for conformal contact with the cortical surface is reported. The injectable sensor array, composed of graphene multi-channel electrodes for neural recording and electrical stimulation and MoS2-based sensors for monitoring intracranial temperature and pressure, is designed based on a mesh structure whose elasticrestoringforce enables the contracted device to spread out. It is demonstrated that the sensor array injected into a rabbit's head can detect epileptic discharges on the surface of the cortex and mitigate it by electrical stimulation while monitoring both intracranial temperature and pressure. This method providesgoodpotentialfor implanting a variety of functional devices via minimally invasive surgery.

Changes in preBötzinger Complex neuron discharge associated with changes in PCO2 in decerebrate rabbits

Background: Maskrey and Nicol reported a strong increase in minute ventilation with increase in PCO2 (J Physiol 1980, 301: 49-58). We investigated a) whether there was a ceiling to this effect at high CO2 levels and b) whether the change in ventilation was associated with specific changes in respiratory neurons in the preBötzinger complex (preBC). Methods: The study was approved by the local Animal Care Committee and conformed to NIH standards. Adult New Zealand White rabbits (3-4 kg) were anesthetized, tracheotomized, ventilated, decerebrated and vagotomized. Phrenic nerve activity was recorded from the C5 rootlet, time averaged and used to calculate inspiratory (TI) and expiratory durations (TE) and peak phrenic activity (PPA). PPA was normalized to the value at PCO2 50mmHg. Individual neurons were recorded in the functionally identified preBC using multichannel electrodes at increasing CO2 levels. Statistical analysis used the Wilcoxon signed-rank test to determine changes in respiratory parameters between CO2 levels and Friedman RM-ANOVA to determine changes in neuronal discharge frequency (Fn). A generalized linear mixed model was used to determine associations between CO2-dependent changes in TI, TE, PPA, and changes in Fn for different neuron types. p&lt;0.05 indicated a significant difference. Results: In 34 animals, the increase in minute ventilation with increasing PCO2 was due mostly to the change in PPA. The increase in respiratory rate was due mostly to a decrease in TE. There was little increase in respiratory output at PCO2 &gt; 50 mmHg. In 209 neurons, increasing PCO2 increased Fn in inspiratory augmenting (I aug, n= 70, p&lt;0.0001 for CO2 30 vs 40 and 40 vs 50mmHg), I parabolic (I para, n=43, p&lt;0.0001 for CO2 40 vs 50 mmHg), pre-inspiratory (pre-I, n=35, p&lt;0.01 for CO2 30 vs 40 mmHg), and expiratory decrementing (E dec, n=44, p&lt;0.01 for CO2 40 vs 50 mmHg) neurons, but not in I dec (n=8) and non-respiratory modulated (NRM, n=9) neurons. The strongest correlation was found between the changes in phase timing and PPA and Fn in I aug and pre-I neurons. Conclusion: We found a ceiling effect to the increase in respiratory output at PCO2 levels &gt; 50 mmHg. Inspiratory preBC neuron subtypes were more affected by the changes in PCO2. NIH R01HL159546. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Evaluation of an online SSVEP-BCI with fast system setup

The brain–computer interface (BCI) plays an important role in neural restoration. Current BCI systems generally require complex experimental preparation to perform well, but this time-consuming process may hinder their use in clinical applications. To explore the feasibility of simplifying the BCI system setup, a wearable BCI system based on the steady-state visual evoked potential (SSVEP) was developed and evaluated. Fifteen healthy participants were recruited to test the fast-setup system using dry and wet electrodes in a real-life scenario. In this study, the average system setup time for the dry electrode was 38.40 seconds and that for the wet electrode was 103.40 seconds, which are times appreciably shorter than those in previous BCI experiments, enabling a rapid setup of the BCI system. Although the electroencephalogram (EEG) signal quality was low in this fast-setup BCI experiment, the BCI system achieved an information transfer rate of 138.89 bits/min with an eight-channel wet electrode and an information transfer rate of 70.59 bits/min with an eight-channel dry electrode, showing that the overall performance was close to that in traditional experiments. In addition, the results suggest that the solutions of a multi-channel dry electrode or few-channel wet electrode may be suitable for the fast-setup SSEVP-BCI. This fast-setup SSVEP-BCI has the advantages of simple preparation and stable performance and is thus conducive to promoting the use of the BCI in clinical practice.

An optrode array for spatiotemporally-precise large-scale optogenetic stimulation of deep cortical layers in non-human primates

Optogenetics has transformed studies of neural circuit function, but remains challenging to apply to non-human primates (NHPs). A major challenge is delivering intense, spatiotemporally-precise, patterned photostimulation across large volumes in deep tissue. Such stimulation is critical, for example, to modulate selectively deep-layer corticocortical feedback circuits. To address this need, we have developed the Utah Optrode Array (UOA), a 10×10 glass needle waveguide array fabricated atop a novel opaque optical interposer, and bonded to an electrically addressable µLED array. In vivo experiments with the UOA demonstrated large-scale, spatiotemporally precise, activation of deep circuits in NHP cortex. Specifically, the UOA permitted both focal (confined to single layers/columns), and widespread (multiple layers/columns) optogenetic activation of deep layer neurons, as assessed with multi-channel laminar electrode arrays, simply by varying the number of activated µLEDs and/or the irradiance. Thus, the UOA represents a powerful optoelectronic device for targeted manipulation of deep-layer circuits in NHP models.

A novel multi-channel porous structure facilitating mass transport towards highly efficient alkaline water electrolysis

An advantageous porous architecture of electrodes is pivotal in significantly enhancing alkaline water electrolysis (AWE) efficiency by optimizing the mass transport mechanisms. This effect becomes even more pronounced when aiming to achieve elevated current densities. Herein, we employed a rapid and scalable laser texturing process to craft novel multi-channel porous electrodes. Particularly, the obtained electrodes exhibit the lowest Tafel slope of 79 mV dec−1 (HER) and 49 mV dec−1 (OER). As anticipated, the alkaline electrolyzer (AEL) cell incorporating multi-channel porous electrodes (NP-LT30) exhibited a remarkable improvement in cell efficiency, with voltage drops (from 2.28 to 1.97 V) exceeding 300 mV under 1 A cm−1, compared to conventional perforated Ni plate electrodes. This enhancement mainly stemmed from the employed multi-channel porous structure, facilitating mass transport and bubble dynamics through an innovative convection mode, surpassing the traditional convection mode. Furthermore, the NP-LT30-based AEL cell demonstrated exceptional durability for 300 h under 1.0 A cm−2. This study underscores the capability of the novel multi-channel porous electrodes to expedite mass transport in practical AWE applications.

Resistivity tomography based on multichannel electrodes

Resistivity tomography based on multichannel electrodes

Transparent vertical nanotube electrode arrays on graphene for cellular recording and optical imaging

Here, we report the fabrication of transparent multichannel vertical nanotube electrode arrays for detecting cellular activity and optically imaging neuronal networks. To fabricate these transparent electrode arrays, position- and morphology-controlled ZnO nanotube arrays consisting of ultrathin nanowalls were grown on transparent graphene layers and coated with Ti/Au metal layers. Using these multichannel arrays, electrophysiological signals were individually recorded from primary mouse hippocampal neurons and recorded distinctive intracellular potential-like signals. Moreover, the transparent electrode array enabled fluorescence imaging of neuron cell bodies and neurite connections. This transparent graphene- and nanotube-based recording device is proposed to greatly increase the versatility of capabilities for investigating neuronal activity through simultaneous recording and imaging of neuron cultures.

A soft, scalable and adaptable multi-contact cuff electrode for targeted peripheral nerve modulation

BackgroundCuff electrodes target various nerves throughout the body, providing neuromodulation therapies for motor, sensory, or autonomic disorders. However, when using standard, thick silicone cuffs, fabricated in discrete circular sizes, complications may arise, namely cuff displacement or nerve compression, due to a poor adaptability to variable nerve shapes and sizes encountered in vivo. Improvements in cuff design, materials, closing mechanism and surgical approach are necessary to overcome these issues.MethodsIn this work, we propose a microfabricated multi-channel silicone-based soft cuff electrode with a novel easy-to-implant and size-adaptable design and evaluate a number of essential features such as nerve-cuff contact, nerve compression, cuff locking stability, long-term integration and stimulation selectivity. We also compared performance to that of standard fixed-size cuffs.ResultsThe belt-like cuff made of 150 μm thick silicone membranes provides a stable and pressure-free conformal contact, independently of nerve size variability, combined with a straightforward implantation procedure. The adaptable design and use of soft materials lead to limited scarring and demyelination after 6-week implantation. In addition, multi-contact designs, ranging from 6 to 16 electrodes, allow for selective stimulation in models of rat and pig sciatic nerve, achieving targeted activation of up to 5 hindlimb muscles.ConclusionThese results suggest a promising alternative to classic fixed-diameter cuffs and may facilitate the adoption of soft, adaptable cuffs in clinical settings.

Multi-Channel Soft Dry Electrodes for Electrocardiography Acquisition in the Ear Region.

In-ear acquisition of physiological signals, such as electromyography (EMG), electrooculography (EOG), electroencephalography (EEG), and electrocardiography (ECG), is a promising approach to mobile health (mHealth) due to its non-invasive and user-friendly nature. By providing a convenient and comfortable means of physiological signal monitoring, in-ear signal acquisition could potentially increase patient compliance and engagement with mHealth applications. The development of reliable and comfortable soft dry in-ear electrode systems could, therefore, have significant implications for both mHealth and human-machine interface (HMI) applications. This research evaluates the quality of the ECG signal obtained with soft dry electrodes inserted in the ear canal. An earplug with six soft dry electrodes distributed around its perimeter was designed for this study, allowing for the analysis of the signal coming from each electrode independently with respect to a common reference placed at different positions on the body of the participants. An analysis of the signals in comparison with a reference signal measured on the upper right chest (RA) and lower left chest (LL) was performed. The results show three typical behaviors for the in-ear electrodes. Some electrodes have a high correlation with the reference signal directly after inserting the earplug, other electrodes need a settling time of typically 1-3 min, and finally, others never have a high correlation. The SoftPulseTM electrodes used in this research have been proven to be perfectly capable of measuring physiological signals, paving the way for their use in mHealth or HMI applications. The use of multiple electrodes distributed in the ear canal has the advantage of allowing a more reliable acquisition by intelligently selecting the signal acquisition locations or allowing a better spatial resolution for certain applications by processing these signals independently.

Effect Analysis of Wearing an Lumbar Exoskeleton on Coordinated Activities of the Low Back Muscles Using sEMG Topographic Maps.

Lumbar exoskeleton has potential to assist in lumbar movements and thereby prevent impairment of back muscles. However, due to limitations of evaluation tools, the effect of lumbar exoskeletons on coordinated activities of back muscles is seldom investigated. This study used the surface electromyography (sEMG) topographic map based on multi-channel electrodes from low back muscles to analyze the effects. Thirteen subjects conducted two tasks, namely lifting and holding a 20kg-weight box. For each task, three different trials, not wearing exoskeleton (NoExo), wearing exoskeleton but power-off (OffExo), and wearing exoskeleton and power-on (OnExo), were randomly conducted. Root-mean-square (RMS) and median-frequency (MDF) topographic maps of the recorded sEMG were constructed. Three parameters, average pixel values, distribution of center of gravity (CoG), and entropy, were extracted from the maps to assess the muscle coordinated activities. In the lifting task, results showed the average pixel values of RMS maps for the NoExo trial were lower than those for the OffExo trial ( [Formula: see text]) but the same as those for the OnExo trial ( [Formula: see text]0.05). The distribution of CoG showed a significant difference between NoExo and OnExo trials ( [Formula: see text]). In the holding task, RMS and MDF maps' average pixel values showed significant differences between NoExo and OnExo trials ( [Formula: see text]). These findings suggest that active lumbar exoskeletons can reduce the load on low back muscles in the static holding task rather than in the dynamic lifting task. This proves sEMG topographic maps offer a new way to evaluate such effects, thereby helping improve the design of lumbar exoskeleton systems.