IEEE Sensors Journal, Journal Year: 2024, Volume and Issue: 24(17), P. 27142 - 27151
Published: July 22, 2024
Language: Английский
Cyborg and Bionic Systems, Journal Year: 2025, Volume and Issue: 6
Published: Jan. 1, 2025
Materials that establish functional, stable interfaces to targeted tissues for long-term monitoring/stimulation equipped with diagnostic/therapeutic capabilities represent breakthroughs in biomedical research and clinical medicine. A fundamental challenge is the mechanical chemical mismatch between implants ultimately results device failure corrosion by biofluids associated foreign body response. Of particular interest development of bioactive materials at level chemistry mechanics high-performance, minimally invasive function, simultaneously tissue-like compliance vivo biocompatibility. This review summarizes most recent progress these purposes, an emphasis on material properties such as response, integration schemes biological tissues, their use bioelectronic platforms. The article begins overview emerging classes platforms bio-integration proven utility live animal models, high performance different form factors. Subsequent sections various flexible, soft materials, ranging from self-healing hydrogel/elastomer bio-adhesive composites materials. Additional discussions highlight examples active systems support electrophysiological mapping, stimulation, drug delivery treatments related diseases, spatiotemporal resolutions span cellular organ-scale dimension. Envisioned applications involve advanced brain, cardiac, other organ systems, offer stability human subjects models. Results will inspire continuing advancements functions benign thus yielding therapy diagnostics healthcare.
Language: Английский
Citations
2
Applied Sciences, Journal Year: 2025, Volume and Issue: 15(1), P. 392 - 392
Published: Jan. 3, 2025
Brain–computer interface (BCI) technologies for language decoding have emerged as a transformative bridge between neuroscience and artificial intelligence (AI), enabling direct neural–computational communication. The current literature provides detailed insights into individual components of BCI systems, from neural encoding mechanisms to paradigms clinical applications. However, comprehensive perspective that captures the parallel evolution cognitive understanding technological advancement in BCI-based remains notably absent. Here, we propose Interpretation–Communication–Interaction (ICI) architecture, novel three-stage an analytical lens examining development. Our analysis reveals field’s basic signal interpretation through dynamic communication intelligent interaction, marked by three key transitions: single-channel multimodal processing, traditional pattern recognition deep learning architectures, generic systems personalized platforms. This review establishes has achieved substantial improvements regard system accuracy, latency reduction, stability, user adaptability. proposed ICI architecture bridges gap computational methodologies, providing unified evolution. These offer valuable guidance future innovations their practical application assistive contexts.
Language: Английский
Citations
1
Journal of Neuroscience Methods, Journal Year: 2024, Volume and Issue: 405, P. 110108 - 110108
Published: March 6, 2024
Language: Английский
Citations
5
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Journal Year: 2024, Volume and Issue: 32, P. 1355 - 1369
Published: Jan. 1, 2024
Nowadays, numerous countries are facing the challenge of aging population. Additionally, number people with reduced mobility due to physical illness is increasing. In response this issue, robots used for walking assistance and sit-to-stand (STS) transition have been introduced in nursing assist these individuals walking. Given shared characteristics robots, paper collectively refers them as Walking Support Robots (WSR). service assisting functions included scope review. WSR a crucial element modern assistants received significant research attention. Unlike passive walkers that require much user's strength move, can autonomously perceive state user environment, select appropriate control strategies maintaining balance movement. This offers comprehensive review recent literature on WSR, encompassing an analysis structure design, perception methods, safety & comfort features. conclusion, it summarizes key findings, current challenges discusses potential future directions field.
Language: Английский
Citations
4
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Journal Year: 2025, Volume and Issue: 33, P. 420 - 430
Published: Jan. 1, 2025
Expanding the application possibilities of brain-computer interfaces (BCIs) is possible through their implementation in mixed reality (MR) environments. However, visual stimuli are displayed against a realistic scene MR environment, which degrades BCI performance. The purpose this study was to optimize stimulus colors order improve MR-BCI system's In 10-command SSVEP-BCI deployed. Various and background for system were tested optimized offline online experiments. Color contrast ratios (CCRs) between introduced assess performance difference among all conditions. Additionally, we proposed cross-correlation task-related component analysis based on simulated annealing (SA-xTRCA), can increase signal-to-noise ratio (SNR) detection accuracy by aligning SSVEP trials. results an experiment showed that had significant interaction effect impact A nonlinear relationship CCR value exists. Online demonstrated performed best with polychromatic colored background. SA-xTRCA significantly outperformed other four traditional algorithms. average information transfer rate (ITR) achieved 57.58 ± 5.31 bits/min. This proved be effectively enhanced optimizing color color. environments, used as quantitative criterion choosing design.
Language: Английский
Citations
0
Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 63 - 79
Published: Jan. 1, 2025
Language: Английский
Citations
0
Frontiers in Human Neuroscience, Journal Year: 2025, Volume and Issue: 19
Published: Feb. 6, 2025
Understanding how the brain encodes upper limb movements is crucial for developing control mechanisms in assistive technologies. Advances technologies, particularly Brain-machine Interfaces (BMIs), highlight importance of decoding motor intentions and kinematics effective control. EEG-based BMI systems show promise due to their non-invasive nature potential inducing neural plasticity, enhancing rehabilitation outcomes. While BMIs intention kinematics, studies indicate inconsistent correlations with actual or planned movements, posing challenges achieving precise reliable prosthesis Further, variability predictive EEG patterns across individuals necessitates personalized tuning improve efficiency. Integrating multiple physiological signals could enhance precision reliability, paving way more strategies. Studies have shown that activity adapts gravitational inertial constraints during movement, highlighting critical role adaptation biomechanical changes creating devices. This review aims provide a comprehensive overview recent progress deciphering associated both assisted avenues future exploration neurorehabilitation brain-machine interface development.
Language: Английский
Citations
0
Journal of Neural Engineering, Journal Year: 2025, Volume and Issue: 22(2), P. 026012 - 026012
Published: March 11, 2025
Abstract Objective. Advances in electronics and materials science have led to the development of sophisticated components for clinical research neurotechnology systems. However, instrumentation easily evaluate how these function a complete system does not yet exist. In this work, we set out design validate software-defined mixed-signal routing fabric, ‘xDev’, that enables designers rapidly iterate, evaluate, deploy advanced multi-component Approach. We developed requirements xDev, implemented based on 16 × analog crosspoint multiplexer. then tested impedance switching characteristics design, assessed signal gain crosstalk attenuation across biological high-speed digital signaling frequencies, evaluated ability xDev flexibly reroute microvolt-scale amplitude signals. Finally, conducted an intraoperative vivo deployment conduct neuromodulation experiments using diverse submodules. Main results. The matching, attenuation, frequency response accurately transmitted signals over broad range encapsulating features typical biosignals extending into ranges. Microvolt-scale 600 Mbps Ethernet connections were routed through fabric. These performance culminated demonstration flexibility via implanted spinal electrode arrays ovine model. Significance. represents first-of-its-kind, low-cost, accelerator platform. Through public, open-source distribution our designs, lower obstacles facing future
Language: Английский
Citations
0
Cyborg and Bionic Systems, Journal Year: 2025, Volume and Issue: 6
Published: Jan. 1, 2025
Primates possess a more developed central nervous system and higher level of intelligence than rodents. Detecting modulating deep brain activity in primates enhances our understanding neural mechanisms, facilitates the study major diseases, enables brain–computer interactions, supports advancements artificial intelligence. Traditional imaging methods such as magnetic resonance imaging, positron emission computed tomography, scalp electroencephalogram are limited spatial resolution. They cannot accurately capture signals from individual neurons. With progress microelectromechanical systems other micromachining technologies, single-neuron detection stimulation technology rodents based on microelectrodes has made important progress. However, compared with rodents, human nonhuman have larger volume that needs deeper implantation depth, test object safety device preparation requirements. Therefore, high-resolution devices suitable for long-term brains urgently needed. This paper reviewed electrode array used electrophysiological electrochemical detections primates’ brains. The research recording technologies was introduced perspective type structures, their potential value neuroscience clinical disease treatments discussed. Finally, it is speculated future electrodes will lot room development terms flexibility, high resolution, brain, throughput. improvements forms process expand activities, bring new opportunities challenges further neuroscience.
Language: Английский
Citations
0
APL Bioengineering, Journal Year: 2025, Volume and Issue: 9(2)
Published: April 16, 2025
Neural signal degradation poses a significant challenge in maintaining stable performance when decoding motor tasks using multiunit activity (MUA) and local field potential (LFP) signals the implantable brain machine interface (iBMI) applications. Effective methods for imputing degraded or missing are essential to restore neural integrity, thereby improving accuracy system robustness over long-term recordings with fluctuating quality. This study introduces confidence-weighted Bayesian linear regression (CW-BLR) approach impute affected by degradation, enhancing consistency of decoding. The CW-BLR was compared traditional methods—mean imputation (Mean-imp) Gaussian-mixture-model-based expectation–maximization (GMM-EM)—using kernel-sliced inverse (kSIR) decoder evaluate outcomes. Four Wistar rats were trained perform forelimb-reaching task while (MUA LFPs) recorded 27 days. imputed during days 8–27. Decoding evaluated kSIR Mean-imp GMM-EM. demonstrated superior effectively preserving both temporal spatial dependencies within signals. CW-BLR-imputed data significantly improved methods, showing consistently higher performance, particularly quality from period. offers robust effective framework iBMI applications, addressing challenges accurate prolonged recordings. By utilizing confidence-based metrics, surpasses providing across scenarios.
Language: Английский
Citations
0