Recovery of heart rate variability after treadmill exercise analyzed by lagged Poincaré plot and spectral characteristics

© 2017 International Federation for Medical and Biological Engineering The aim of this study was to analyze the recovery of heart rate variability (HRV) after treadmill exercise and to investigate the autonomic nervous system response after exercise. Frequency domain indices, i.e., LF(ms 2 ), HF(ms 2 ), LF(n.u.), HF(n.u.) and LF/HF, and lagged Poincaré plot width (SD1 m ) and length (SD2 m ) were introduced for comparison between the baseline period (Pre-E) before treadmill running and two periods after treadmill running (Post-E1 and Post-E2). The correlations between lagged Poincaré plot indices and frequency domain indices were applied to reveal the long-range correlation between linear and nonlinear indices during the recovery of HRV. The results suggested entirely attenuated autonomic nervous activity to the heart following the treadmill exercise. After the treadmill running, the sympathetic nerves achieved dominance and the parasympathetic activity was suppressed, which lasted for more than 4 min. The correlation coefficients between lagged Poincaré plot indices and spectral power indices could separate not only Pre-E and two sessions after the treadmill running, but also the two sessions in recovery periods, i.e., Post-E1 and Post-E2. Lagged Poincaré plot as an innovative nonlinear method showed a better performance over linear frequency domain analysis and conventional nonlinear Poincaré plot

Design of a wearable upper limb rehabilitation robot and its motion simulation and dynamics analysis

Objective: A new wearable upper limb rehabilitation robot is designed to address the disadvantages of the current desktop upper limb rehabilitation robot, which is bulky and inconvenient to move, and the rationality of the design is verified through the analysis of its motion characteristics and the calculation of joint moments. Methods: Firstly, according to the principle of modular design, the overall structure was designed. Secondly, the SOILDWORKS is used for three-dimensional modeling, and the SOILDWORKS Motion is used to simulate the elbow flexion/extension movement, shoulder flexion/extension movement and shoulder-elbow joint linkage movement of the robot. Finally, the dynamic equation of the system is established based on Lagrange method, and the change curve of the joint torque of the manipulator is calculated by MATLAB software. Results: The simulation results confirmed that the motion simulation curves of shoulder joint, elbow joint and wrist joint were smooth. The dynamic analysis confirmed that the joint torque variation curve was smooth and the maximum joint torque was less than the rated torque of the motor after deceleration. Conclusion: The design of wearable upper limb rehabilitation robot is reasonable, which lays a theoretical foundation for the subsequent research on upper limb rehabilitation robot

A study based on functional near-infrared spectroscopy: Cortical responses to music interventions in patients with myofascial pain syndrome

ObjectThis study measured cerebral blood oxygen changes in patients with myofascial pain syndrome (MPS) using functional near-infrared spectroscopy (fNIRS). The aim was to investigate the effect of music intervention on pain relief in MPS patients.Materials and methodsA total of 15 patients with MPS participated in this study. A self-controlled block task design was used to collect the oxy-hemoglobin ([HbO2]) and deoxy-hemoglobin ([HbR]) concentrations in the prefrontal cortex (PFC) and motor cortex using fNIRS. The cerebral cortex response and channel connectivity were further analyzed. In the experiment, the therapist was asked to apply compression of 3–4 kg/cm2 vertically using the thumb to induce pain. Soothing synthetic music with frequencies of 8–150 Hz and 50–70 dB was used as the audio for the music intervention.ResultCompared to the group without music intervention, the activation of brain regions showed a decreasing trend in the group with music intervention under the onset of pain. The results of paired t-tests showed that nine of the data were significantly different (p < 0.05). It was also found that with music intervention, inter-channel connectivity was diminished. Besides, their dorsolateral prefrontal cortex (dlPFC) was significantly correlated with the anterior prefrontal cortex (aPFC) for pain response (r = 0.82), and weakly correlated with the premotor cortex (r = 0.40).ConclusionThis study combines objective assessment indicators and subjective scale assessments to demonstrate that appropriate music interventions can be effective in helping to relieve pain to some extent. The analgesic mechanisms between relevant brain regions under music intervention were explored in depth. New insights into effective analgesic methods and quantitative assessment of pain conditions are presented

An optimization study of estimating blood pressure models based on pulse arrival time for continuous monitoring

Continuous blood pressure (BP) monitoring has a significant meaning for the prevention and early diagnosis of cardiovascular disease. However, under different calibration methods, it is difficult to determine which model is better for estimating BP. This study was firstly designed to reveal a better BP estimation model by evaluating and optimizing different BP models under a justified and uniform criterion, i.e., the advanced point-to-point pairing method (PTP). Here, the physical trial in this study caused the BP increase largely. In addition, the PPG and ECG signals were collected while the cuff bps were measured for each subject. The validation was conducted on four popular vascular elasticity (VE) models (MK-EE, L-MK, MK-BH, and dMK-BH) and one representative elastic tube (ET) model, i.e., M-M. The results revealed that the VE models except for L-MK outperformed the ET model. The linear L-MK as a VE model had the largest estimated error, and the nonlinear M-M model had a weaker correlation between the estimated BP and the cuff BP than MK-EE, MK-BH, and dMK-BH models. Further, in contrast to L-MK, the dMK-BH model had the strongest correlation and the smallest difference between the estimated BP and the cuff BP including systolic blood pressure (SBP) and diastolic blood pressure (DBP) than others. In this study, the simple MK-EE model showed the best similarity to the dMK-BH model. There were no significant changes between MK-EE and dMK-BH models. These findings indicated that the nonlinear MK-EE model with low estimated error and simple mathematical expression was a good choice for application in wearable sensor devices for cuff-less BP monitoring compared to others

Research on target localization and adaptive scrubbing of intelligent bathing assistance system

IntroductionBathing is a primary daily activity. Existing bathing systems are limited by their lack of intelligence and adaptability, reliance on caregivers, and the complexity of their control algorithms. Although visual sensors are widely used in intelligent systems, current intelligent bathing systems do not effectively process depth information from these sensors.MethodsThe scrubbing task of the intelligent bath assist system can be divided into a pre-contact localization phase and a post-contact adaptive scrubbing phase. YOLOv5s, known for its ease of deployment and high accuracy, is utilized for multi-region skin detection to identify different body parts. The depth correction algorithm is designed to improve the depth accuracy of RGB-D vision sensors. The 3D position and pose of the target point in the RGB camera coordinate system are modeled and then transformed to the robot base coordinate system by hand-eye calibration. The system localization accuracy is measured when the collaborative robot runs into contact with the target. The self-rotating end scrubber head has flexible bristles with an adjustable length of 10 mm. After the end is in contact with the target, the point cloud scrubbing trajectory is optimized using cubic B-spline interpolation. Normal vectors are estimated based on approximate triangular dissected dyadic relations. Segmented interpolation is proposed to achieve real-time planning and to address the potential effects of possible unexpected movements of the target. The position and pose updating strategy of the end scrubber head is established.ResultsYOLOv5s enables real-time detection, tolerating variations in skin color, water vapor, occlusion, light, and scene. The localization error is relatively small, with a maximum value of 2.421 mm, a minimum value of 2.081 mm, and an average of 2.186 mm. Sampling the scrubbing curve every 2 mm along the x-axis and comparing actual to desired trajectories, the y-axis shows a maximum deviation of 2.23 mm, which still allows the scrubbing head to conform to the human skin surface.DiscussionThe study does not focus on developing complex control algorithms but instead emphasizes improving the accuracy of depth data to enhance localization precision

High corrosion resistance duplex fcc + hcp cobalt based entropic alloys: An experimental and theoretical investigation

A series of duplex fcc + hcp Co-based entropic alloys are being discovered as a new category of entropic alloys with outstanding mechanical properties, especially to overcome a typical mechanical trade-off between strength and ductility. In this work, CALPHAD-based (CALculation of PHAse Diagram) thermodynamic calculations were performed to facilitate alloy design and to understand corrosion behaviors. The kinetics of the electrochemical corrosion for designed alloys in typical aggressive anion Cl- was investigated by electrochemical tests, including open circuit potential (OCP), polarization and cyclic polarization curves, and electrochemical impedance spectroscopy (EIS). The valence state and the surface morphologies of the passive films were investigated by X-ray photoelectron spectroscopy (XPS) and atomic force microscope (AFM). High corrosion resistance materials with high strength and ductility performances were discovered in the present work. Except for Ni-oxides, various spinel compounds and many other oxides including Co2O3, Cr2O3, Fe2O3, MnO, MoO3, CoCr2O4, FeCr2O4, CoFe2O4, and CoMoO4 were observed in the passive films. The adsorbed and penetrated corrosive anion Cl- will be prone to breakdown the passive films with less Cr2O3, CoCr2O4 and MoO3 to form pitting corrosion (also include other localized corrosion, such as intergranular corrosion and crevice corrosion). The microstructure of the hcp martensite with the fcc matrix has played an important role in the propagation of the localized anodic dissolution in the form of cleavage and quasi-cleavage. The theoretical calculations are in good agreement with the experimental observations. This paper paves a way for the future development of high-performance Co-based entropic alloys served in some harsh environments

Research on adaptive impedance control technology of upper limb rehabilitation robot based on impedance parameter prediction

Introduction: With the aggravation of aging and the growing number of stroke patients suffering from hemiplegia in China, rehabilitation robots have become an integral part of rehabilitation training. However, traditional rehabilitation robots cannot modify the training parameters adaptively to match the upper limbs’ rehabilitation status automatically and apply them in rehabilitation training effectively, which will improve the efficacy of rehabilitation training.Methods: In this study, a two-degree-of-freedom flexible drive joint rehabilitation robot platform was built. The forgetting factor recursive least squares method (FFRLS) was utilized to estimate the impedance parameters of human upper limb end. A reward function was established to select the optimal stiffness parameters of the rehabilitation robot.Results: The results confirmed the effectiveness of the adaptive impedance control strategy. The findings of the adaptive impedance control studies showed that the adaptive impedance control had a significantly greater reward than the constant impedance control, which was in line with the simulation results of the variable impedance control. Moreover, it was observed that the levels of robot assistance could be suitably modified based on the subject’s different participation.Discussion: The results facilitated stroke patients’ upper limb rehabilitation by enabling the rehabilitation robot to adaptively change the impedance parameters according to the functional status of the affected limb. In clinic therapy, the proposed control strategy may help to adjust the reward function for different patients to improve the rehabilitation efficacy eventually

A multi-degree-of-freedom reconfigurable ankle rehabilitation robot with adjustable workspace for post-stroke lower limb ankle rehabilitation

Introduction: A multi-degree-of-freedom ankle rehabilitation robot with an adjustable workspace has been designed to facilitate ankle joint rehabilitation training. It features a rotation center adapted to the human body, making it suitable for patients with ankle dysfunction following a stroke.Method: In this study, a multi-degree-of-freedom reconfigurable ankle rehabilitation robot (RARR) with adaptable features, based on the principles of ergonomics, has been proposed to cater to the varying needs of patients. This robot offers an adjustable workspace, allowing for different types of ankle joint rehabilitation exercises to be performed. By adjusting the assembly of the RARR, personalized and targeted training can be provided to patients, circumventing issues of redundancy in degrees of freedom during its use. A kinematic model of the robot has been established, and finite element simulation has been employed to analyze the strength of critical components, ensuring the safety of the robot. An experimental platform has been set up to assess the smoothness of the rehabilitation process with RARR, with angle measurements conducted using an Inertial Measurement Unit (IMU).Results and discussion: In conclusion, both simulation and experimental results demonstrate that the robot offers an adjustable workspace and exhibits relatively smooth motion, thereby confirming the safety and effectiveness of the robot. These outcomes align with the intended design goals, facilitating ankle joint rehabilitation and advancing the field of reconfigurable robotics. The RARR boasts a compact structure and portability, making it suitable for various usage scenarios. It is easily deployable for at-home use by patients and holds practical application value for wider adoption in rehabilitation settings

Gait phase recognition of children with cerebral palsy via deep learning based on IMU data from a soft ankle exoskeleton

Accurate gait-phase identification in children with Cerebral Palsy (CP) constitutes a pivotal prerequisite for evidence-based rehabilitation. Addressing the precise detection of gait disturbances under natural ambulation, we propose a deep-learning framework that integrates a stacked denoising autoencoder (SDA) with a long short-term memory network (SDA–LSTM) to classify four canonical gait phases. A community-oriented dataset was constructed by synchronizing ankle-mounted inertial measurement units (IMU) with plantar-pressure insoles; natural gait sequences of six children with mild CP were acquired in open environments. The SDA layer robustly extracts discriminative representations from non-stationary, high-noise signals, whereas the LSTM module models inter-phase temporal dependencies, thereby enhancing generalization cross-user. In noise-free conditions the SDA–LSTM framework attained 97.83% accuracy, significantly exceeding SVM (94.68%), random forest (96.05%), and standalone LSTM (95.86%). Under additive Gaussian noise with SNR ranging from 5 to 30 dB, the model preserved stable performance; at 10 dB SNR (Signal-to-Noise Ratio), accuracy remained 90.96%, corroborating its exceptional robustness. These findings demonstrate that SDA–LSTM effectively handles the complex, heterogeneous gait patterns of children with CP and is readily deployable for clinical assessment and exoskeletal assistance systems, indicating substantial translational potential