IEEE Transactions on Biomedical Engineering最新文献

Objective: Gait asymmetry may be improved through various gait training methods. Combining split-belt treadmill walking (SB) with visual feedback distortion (VD) could enhance motor learning, thereby improving gait symmetry adaptation and retention. This study compared step length symmetry adaptation and aftereffects between SB-only and the combined explicit VD with SB, as well as between explicit VD-only and the combined explicit VD with SB.

Method: Trials consisted of a 28-minute walking with three phases: a 3-minute baseline, a 10-minute adaptation, and a 15-minute post-adaptation. In the VD trial, two bars representing the right and left step lengths were displayed. The length of the right bar gradually decreased by 3% during the adaptation period, prompting participants to consciously correct their steps to match the heights of the two bars. In the SB trial, the speed of the right treadmill belt was incrementally increased by 5%. The VD+SB trial combined both perturbations. After the removal of these perturbations, the aftereffect of the adapted asymmetric step length was evaluated in the post-adaptation period.

Results: During the adaptation period, the step length symmetry ratio shifted negatively in the SB trial, while it increased positively in the VD trial, indicating longer right steps than left. In the VD+SB trial, subjects extended their right step more than their left. Notably, the VD+SB trial demonstrated a longer aftereffect compared to both the SB-only and VD-only trials.

Conclusion: The visual distortion paradigm can be explicitly applied and integrated with split-belt treadmill walking to enhance the efficacy of symmetric gait adaptation, resulting in more sustained effects on the retention of newly learned motor patterns.

Electrodermal activity (EDA), commonly measured as skin conductance (SC), is a widely used physiological signal in psychological research and behavioral health applications. EDA is considered an indicator of arousal, a key aspect of emotion and stress. This work proposes a data-driven dynamic system model that characterizes the temporal dynamics of skin conductance and infers the latent arousal signal, utilizing techniques from system identification and sparse optimization. It introduces a fourth-order, linear time-invariant model for the overall skin conductance signal, including both the tonic and phasic components. The model was applied to a large dataset of over 200 participants to evaluate model fit. Furthermore, a three-component decomposition of skin conductance is introduced, based on mathematical definitions derived from the model, which provides key insights into the temporal dynamics of skin conductance. Comparative evaluation shows that the estimated latent neural signal effectively differentiates between high and low arousal states, while maintaining expected physiological properties. This work lays the foundation for numerous behavioral health applications and paves the road for designing physiology-based interventions aimed at regulating arousal.

Objective: A promising avenue for vision restoration against retinal degeneration is the use of semiconductor-based photovoltaic biointerfaces to substitute natural photoreceptors. Instead of silicon, perovskite has emerged as an exciting material for solar energy harvesting, and its nanocrystalline forms generally offer better stability than their bulk counterparts in addition to the distinct synthesis and fabrication steps.

Methods: Herein, we synthesize tetramethylammonium lead iodide (TMAPbI3) perovskite quantum dots (QDs) as a novel photoactive material for photovoltaic biointerfaces. While the TMAPbI3 quantum dots and electrolyte interface induces Faradaic photocurrent under light illumination, the heterojunction with P3HT converts the charge-transfer process to a safe capacitive photocurrent with an improved ionic responsivity of 17.4 mA/W.

Significance: The integration of the 18-nm quantum dot thickness shows good biocompatibility with primary cultures of hippocampal neurons and the photoresponse of the biointerface triggered photostimulation of the neurons. The rise of perovskite materials can stimulate novel forms of photovoltaic retina implants.

Objective: Functional vascular imaging is a critical method for early detection and prevention of disease. Established non-contact vascular imaging techniques capture predominantly structural information. In this study, a novel non-contact label-free in vivo Photon Absorption Remote Sensing (PARS) microscope is developed for structural and functional vascular imaging.

Methods: The presented in vivo PARS microscope captures the endogenous absorption of green (532nm) light to form a complete picture of vasculature and surrounding tissues. Imaging system repeatability is enhanced through robust transient absorption signal extraction, and state-of-the-art real-time alignment methods.

Results: Detailed imaging of vascular structure is demonstrated through in vivo microscopy of two established animal models: mouse ear and chicken embryo. Preliminary functional contrast is realized through video rate imaging of red blood cell dynamics in the capillary networks of chicken embryos.

Conclusion: The presented in vivo PARS microscope successfully captures detailed structural and functional vascular contrast.

Significance: This innovative non-contact label-free imaging technique holds promise as a tool for preventative medical care, as functional change often precedes structural change.

Objective: Ventricular arrhythmias are the primary arrhythmias that cause sudden cardiac death. We address the problem of classification between ventricular tachycardia (VT), ventricular fibrillation (VF) and non-ventricular rhythms (NVR).

Methods: To address the challenging problem of the discrimination between VT and VF, we develop similarity maps - a novel set of features designed to capture regularity within an ECG trace. These similarity maps are combined with features extracted through learnable Parzen band-pass filters and derivative features to discriminate between VT, VF, and NVR. To combine the benefits of these different features, we propose a hierarchical multi-stream ResNet34 architecture.

Results: Our empirical results demonstrate that the similarity maps significantly improve the accuracy of distinguishing between VT and VF. Overall, the proposed approach achieves an average class sensitivity of 89.68%, and individual class sensitivities of 81.46% for VT, 89.29% for VF, and 98.28% for NVR.

Conclusion: The proposed method achieves a high accuracy of ventricular arrhythmia detection and classification.

Significance: Correct detection and classification of ventricular fibrillation and ventricular tachycardia are essential for effective intervention and for the development of new therapies and translational medicine.

Deep brain stimulation (DBS) is an established treatment for neurodegenerative movement disorders such as Parkinson's disease that mitigates symptoms by overwriting pathological signals from the central nervous system to the motor system. Nearly all computational models of DBS, directly or indirectly, associate clinical improvements with the extent of fiber activation in the vicinity of the stimulating electrode. However, it is not clear how such activation modulates information transmission. Here, we use the exact cable equation for straight or curved axons and show that DBS segregates the signaling pathways into one of the three communicational modes: complete information blockage, uni-, and bi-directional transmission. Furthermore, all these modes respond to the stimulating pulse in an asynchronous but frequency-locked fashion. Asynchrony depends on the geometry of the axon, its placement and orientation, and the stimulation protocol. At the same time, the electrophysiology of the nerve determines frequency-locking. Such a trimodal response challenges the notion of activation as a binary state and studies that correlate it with the DBS outcome. Importantly, our work suggests that a mechanistic understanding of DBS action relies on distinguishing between these three modes of information transmission.

Objective: Suspended loads have been shown to improve loaded-walking economy. Establishing a biped walking model with dynamic trunk pitch angles can provide more comprehensive estimates of the human biomechanical response under suspended loads.

Methods: We developed the trunk-load- hip dynamics, modified the spring-loaded-inverted-pendulum (SLIP) model, and optimized the loaded-walking pattern for minimal energetic cost. 9 subjects participated in experiments using a powered backpack to validate the model's performance, conducting two trials: Load-Suspended (LS) and Load-Locked (LL).

Results: The averaged correlation coefficient of simulated and experimental hip trajectory, vertical and horizontal GRFs, and individual leg mechanical (ILM) powers are 0.96, 0.97, 0.93, and 0.81, respectively. The RMS error between simulated and experimental peaks of vertical GRFs, braking peaks of horizontal GRFs, and energetic costs was under 10%. Simulation also provides observation on the effect of suspended load on dynamic trunk pitch angles and torques, and leg stiffness. Both the simulation and experiment demonstrated the advantages of LS in reducing GRFs and energetic cost. Additionally, the simulation shows the peaks of trunk flexion and extension torque are reduced by 34.77% (p<0.05) and 37.88% (p<0.05) in LS.

Conclusion: The model effectively estimates hip trajectory, vertical and horizontal GRFs, ILM powers, and energetic cost, and provides observations on trunk behavior under different load conditions. The model also supports the advantages of suspension load.

Significance: Appropriate models could comprehensively reveal the mechanism between the mechanical systems and human biomechanics responses, guide the design of carrying load devices, and provide rapid evaluation of its effects.

Objective: High-frequency stimulation (HFS) of electrical pulse sequences has been used in various neuromodulation techniques to treat certain disorders. Here, we test the hypothesis that HFS sequences with purely periodic pulses could directly generate non-uniform firing in directly stimulated neurons.

Methods: In vivo experiments were conducted in the rat hippocampal CA1 region. A stimulation electrode was placed on the alveus fibers, and a recording electrode array was inserted into the CA1 region upstream of the stimulation site. Antidromic-HFS (A-HFS) of 100 Hz pulses was applied to the alveus to antidromically activate the soma of pyramidal neurons around the recording site. By minimizing the interferences of population spikes, the evoked unit spikes of individual pyramidal neurons were obtained during A-HFS. Additionally, a computational model of pyramidal neuron was used to simulate the neuronal responses to A-HFS, revealing possible mechanisms underlying the different firing patterns.

Results: Of the total 54 pyramidal neurons recorded during 2-min 100 Hz A-HFS, 38 (70%) neurons fired in a cluster pattern with alternating periods of intensive spikes and silence. The remaining 16 (30%) neurons fired in a non-cluster pattern with regular spikes. Modeling simulations showed that under the situation of HFS-induced intermittent block, conduction failure and generation failure of action potentials along the axons resulted in the cluster and non-cluster firing.

Conclusion: Sustained axonal A-HFS with periodic pulses can induce non-uniform firing in directly stimulated neurons.

Significance: This finding provides new evidence for the nonlinear dynamics of neuronal firing, even under uniform stimulation.

Objective: The Motor Imagery (MI) paradigm has been widely used in brain-computer interface (BCI) for device control and motor rehabilitation. However, the MI paradigm faces challenges such as comprehension difficulty and limited decoding accuracy. Therefore, we propose the Action Observation with Rhythm Imagery (AORI) as a natural paradigm to provide distinct features for high-performance decoding.

Methods: Twenty subjects were recruited in the current study to perform the AORI task. Spectral-spatial, temporal and time-frequency analyses were conducted to investigate the AORI-activated brain pattern. Task-discriminant component analysis (TDCA) was utilized to perform multiclass motor decoding.

Results: The results demonstrated distinct lateralized ERD in the alpha and beta bands, and clear lateralized steady-state movement-related rhythm (SSMRR) at the movement frequencies and their first harmonics. The activated brain areas included frontal, sensorimotor, posterior parietal, and occipital regions. Notably, the decoding accuracy reached 92.16% ± 7.61% in the four-class scenario.

Conclusion and significance: We proposed the AORI paradigm, revealed the activated motor-related pattern and proved its efficacy for high-performance motor decoding. These findings provide new possibilities for designing a natural and robust BCI for motor control and motor rehabilitation.

Objective: Infrared Thermography (IRT) has been used to monitor skin temperature variation in a contactless manner, in both clinical medicine and psychophysiology. Here, we introduce a new methodology to obtain information about autonomic correlates related to perspiration, peripheral vasomotility, and respiration from infrared recordings.

Methods: Our approach involves a model-based decomposition of facial thermograms using Independent Component Analysis (ICA) and an ad-hoc preprocessing procedure. We tested our approach on 30 healthy volunteers whose psychophysiological state was stimulated as part of an experimental protocol.

Results: Within-subject ICA analysis identified three independent components demonstrating correlations with the reference physiological signals. Moreover, a linear combination of independent components effectively predicted each physiological signal, achieving median correlations of 0.9 for electrodermal activity, 0.8 for respiration, and 0.73 for photoplethysmography peaks envelope. In addition, we performed a cross-validated inter-subject analysis, which allows to predict physiological signals from facial thermograms of unseen subjects.

Conclusions/significance: Our findings validate the efficacy of features extracted from both original and thermal-derived signals for differentiating experimental conditions. This outcome emphasizes the sensitivity and promise of our approach, advocating for expanded investigations into thermal imaging within biomedical signal analysis. It underscores its potential for enhancing objective assessments of emotional states.