Synergy Analysis of Back Muscle Activities in Patients with Adolescent Idiopathic Scoliosis Based on High-Density Electromyogram

Symmetrical analysis of paravertebral muscles during superman exercise in patients with adolescent idiopathic scoliosis

BACKGROUND

To investigate the asymmetry of paravertebral muscles during the superman exercise in patients with adolescent idiopathic scoliosis, and to analyze the applicability of this exercise for the rehabilitation of these patients from the perspective of muscle electromyographic activity.

METHODS

37 patients with adolescent idiopathic scoliosis are selected for this study. Surface electromyography signals of the bilateral paravertebral muscles during the daily sitting and the superman exercise are recorded. The differences in Surface electromyography of the bilateral paravertebral muscles are analyzed using the root mean square method and the paraspinal muscle symmetry index.

FINDINGS

The results show that there is no significant difference in the paraspinal muscle symmetry index between the two states. Specifically, 29 patients exhibit the same paraspinal muscle symmetry index, 2 patients have similar indices, and 6 patients display different indices. The root mean square of the convex side paravertebral muscles is generally higher than that of the concave side.

INTERPRETATION

In this study, the activation level of paravertebral muscles during the superman exercise is similar to that during the daily sitting, with the activation level on the convex side being higher than that on the concave side. This indicates that the superman exercise is not suitable for the rehabilitation of patients with adolescent idiopathic scoliosis and may even exacerbate the condition.

Towards Wearable and Portable Spine Motion Analysis Through Dynamic Optimization of Smartphone Videos and IMU Data

BACKGROUND

Monitoring spine kinematics is crucial for applications like disease evaluation and ergonomics analysis. However, the small scale of vertebrae and the number of degrees of freedom present significant challenges for noninvasive and convenient spine kinematics estimation.

METHODS

This study developed a dynamic optimization framework for wearable spine motion tracking at the intervertebral joint level by integrating smartphone videos and Inertia Measurement Units (IMUs) with dynamic constraints from a thoracolumbar spine model. Validation involved motion data from 10 healthy males performing static standing, dynamic upright trunk rotations, and gait. This data included rotations of ten IMUs on vertebrae and virtual landmarks from three smartphone videos preprocessed by OpenCap, an application leveraging computer vision for pose estimation. The kinematic measures derived from the optimized solution were compared against simultaneously collected infrared optical marker-based measurements and in vivo literature data. Solutions only based on IMUs or videos were also compared for accuracy evaluation.

RESULTS

The proposed optimization approach closely matched the reference data in the intervertebral or segmental rotation range, demonstrating minimal angular differences across all motions and the highest correlation in 3D rotations (maximal Pearson and intraclass correlation coefficients of 0.92 and 0.94, respectively). Time-series changes of joint angles also aligned well with the optical-marker reference.

CONCLUSION

Dynamic optimization of the spine simulation that integrates IMUs and computer vision outperforms the single-modality method.

SIGNIFICANCE

This markerless 3D spine motion capture method holds potential for spinal health assessment in large cohorts in real-world settings without dedicated laboratories.

Characterizing upper limb motor dysfunction with temporal and spatial distribution of muscle synergy extracted from high-density surface electromyography

Objective.To promote the development of objective and comprehensive motion function assessment for patients, based on high-density surface electromyography (HD-sEMG), this study investigates the temporal and spatial variations of neuromuscular activities related to upper limb motor dysfunction.Approach.Patients with unilateral upper limb motor dysfunction and healthy controls were enrolled in the study. HD-sEMG was collected from both arms while they were performing eight hand and wrist movements. Muscle synergies were extracted from the HD-sEMG. Symmetry of bilateral upper limb synergies and synergy differences between motions were proposed as spatial indicators to measure alterations in synergy spatial distribution. Additionally, as a temporal characteristic, the correlation of bilateral upper limb activation coefficient was proposed to describe the coordination control of the central nervous system. All temporal and spatial indicators were compared between patients and healthy subjects.Main results.The patients showed a significant decrease (p< 0.05) in the symmetry of bilateral upper limb synergy spatial distribution and correlation of bilateral upper limb activation coefficient. Patients with motor dysfunction also showed an increase in synergy similarity between motions, indicating altered spatial distribution of muscle synergies.Significance.These findings provide valuable insights into specific patterns associated with motor dysfunction, informing motor function assessment, and guiding targeted interventions and rehabilitation strategies for neurologically disordered patients.

Loading Recognition for Lumbar Exoskeleton Based on Multi-Channel Surface Electromyography From Low Back Muscles

Lumbar exoskeleton is an assistive robot, which can reduce the risk of injury and pain in low back muscles when lifting heavy objects. An important challenge it faces involves enhancing assistance with minimal muscle energy consumption. One of the viable solutions is to adjust the force or torque of assistance in response to changes in the load on the low back muscles. It requires accurate loading recognition, which has yet to yield satisfactory outcomes due to the limitations of available measurement tools and load classification methods. This study aimed to precisely identify muscle loading using a multi-channel surface electromyographic (sEMG) electrode array on the low back muscles, combined with a participant-specific load classification method. Ten healthy participants performed a stoop lifting task with objects of varying weights, while sEMG data was collected from the low back muscles using a 3x7 electrode array. Nineteen time segments of the lifting phase were identified, and time-domain sEMG features were extracted from each segment. Participant-specific classifiers were built using four classification algorithms to determine the object weight in each time segment, and the classification performance was evaluated using a 5-fold cross-validation method. The artificial neural network classifier achieved an impressive accuracy of up to 96%, consistently improving as the lifting phase progressed, peaking towards the end of the lifting movement. This study successfully achieves accurate recognition of load on low back muscles during the object lifting task. The obtained results hold significant potential in effectively reducing muscle energy consumption when wearing a lumbar exoskeleton.

Abnormal interlimb coordination of motor developmental delay during infant crawling based on kinematic synergy analysis

BACKGROUND

Previous studies have reported that abnormal interlimb coordination is a typical characteristic of motor developmental delay (MDD) during human movement, which can be visually manifested as abnormal motor postures. Clinically, the scale assessments are usually used to evaluate interlimb coordination, but they rely heavily on the subjective judgements of therapists and lack quantitative analysis. In addition, although abnormal interlimb coordination of MDD have been studied, it is still unclear how this abnormality is manifested in physiology-related kinematic features.

OBJECTIVES

This study aimed to evaluate how abnormal interlimb coordination of MDD during infant crawling was manifested in the stability of joints and limbs, activation levels of synergies and intrasubject consistency from the kinematic synergies of tangential velocities of joints perspective.

METHODS

Tangential velocities of bilateral shoulder, elbow, wrist, hip, knee and ankle over time were computed from recorded three-dimensional joint trajectories in 40 infants with MDD [16 infants at risk of developmental delay, 11 infants at high risk of developmental delay, 13 infants with confirmed developmental delay (CDD group)] and 20 typically developing infants during hands-and-knees crawling. Kinematic synergies and corresponding activation coefficients were derived from those joint velocities using the non-negative matrix factorization algorithm. The variability accounted for yielded by those synergies and activation coefficients, and the synergy weightings in those synergies were used to measure the stability of joints and limbs. To quantify the activation levels of those synergies, the full width at half maximum and center of activity of activation coefficients were calculated. In addition, the intrasubject consistency was measured by the cosine similarity of those synergies and activation coefficients.

RESULTS

Interlimb coordination patterns during infant crawling were the combinations of four types of single-limb movements, which represent the dominance of each of the four limbs. MDD mainly reduced the stability of joints and limbs, and induced the abnormal activation levels of those synergies. Meanwhile, MDD generally reduced the intrasubject consistency, especially in CDD group.

CONCLUSIONS

These features have the potential for quantitatively evaluating abnormal interlimb coordination in assisting the clinical diagnosis and motor rehabilitation of MDD.

Auto-CA: Automated Cobb Angle Measurement Based on Vertebrae Detection for Assessment of Spinal Curvature Deformity

An accurate identification and localization of vertebrae in X-ray images can assist doctors in measuring Cobb angles for treating patients with adolescent idiopathic scoliosis. It is useful for clinical decision support systems for diagnosis, surgery planning, and spinal health analysis. Currently, publicly available annotated datasets on spinal vertebrae are small, making deep-learning-based detection methods that are highly data-dependent less accurate. In this article, we propose an algorithm based on convolutional neural networks that can be trained to detect vertebrae from a small set of images. This method can display critical information on a patient's spine, display vertebrae and their labels on the thoracic and lumbar, calculate the Cobb angle, and evaluate the severity of spinal deformities. The proposed achieved an average accuracy of 0.958 and 0.962 for classifying spinal deformities (i.e., C-shaped, S-shaped type 1, and S-shaped type 2) and severity of Cobb angle (i.e., normal, mild, moderate, and severe), respectively. The Cobb angle measurement had a median difference of less than 5° from the ground-truth with SMAPE of 5.27% and an error on landmark detection of 19.73. In addition, Lenke classification is used to analyze spinal deformities as types A, B, and C, which have an average accuracy of 0.924. Physicians can use the proposed system in clinical practice by providing X-ray images via the user interface.

The back body temperatures of patients with idiopathic scoliosis measured through exercise

BACKGROUND

Aerobic exercise is closely associated with the vital functions of patients with scoliosis. Infrared thermography (IRT) has been increasingly applied in physiological measurements in recent years.

OBJECTIVE

This observational study aimed to use IRT to examine the back body surface temperatures of patients with idiopathic scoliosis during aerobic exercise.

METHODS

Forty-two participants who completed a pre-test were divided into a scoliotic group and a non-scoliotic group. Both groups completed a 30-minute cycling exercise, during which their back body temperature was measured using IRT, and the root-mean-square of the back electromyography value after 30 minutes of aerobic exercise was analyzed.

RESULTS

The back body temperature decreased significantly after 30 minutes of exercise in the non-scoliotic group. In contrast, the back body temperature (at the trapezius and quadratus lumborum muscles) was asymmetric or increased after exercise in the scoliotic group.

CONCLUSIONS

These findings suggest that when patients with scoliosis exercise, their back body temperature should be assessed thoroughly to prevent adverse physiological reactions potentially caused by back body temperature imbalances as well as the potential health problems caused by poor heat dissipation. In addition, such observations can be useful in the early screening of scoliosis.

Exploring Muscle Synergies for Performance Enhancement and Learning in Myoelectric Control Maps

This work proposes two myoelectric control maps based on a DoF-wise synergy algorithm, inspired by human motor control studies. One map, called intuitive, matches control outputs with body movement directions. The second one, named non-intuitive, takes advantage of different synergies contribution to each DoF, without specific correlation to body movement directions. The effectiveness and learning process for the two maps is evaluated through performance metrics in ten able-bodied individuals. The analysis was conducted using a 2-DoFs center-reach-out task and a survey. Results showed equivalent performance and perception for both mappings. However, learning is only visible in subjects that performed better in non-intuitive mapping, that required some familiarization to then exploit its features. Most of the myoelectric control designs use intuitive mappings. Nevertheless, non-intuitive mapping could provide more design flexibility, which can be especially interesting for patients with motor disabilities.

Solvent-Free and Skin-Like Supramolecular Ion-Conductive Elastomers with Versatile Processability for Multifunctional Ionic Tattoos and On-Skin Bioelectronics

The development of stable and biocompatible soft ionic conductors, alternatives to hydrogels and ionogels, will open up new avenues for the construction of stretchable electronics. Here, a brand-new design, encapsulating a naturally occurring ionizable compound by a biocompatible polymer via high-density hydrogen bonds, resulting in a solvent-free supramolecular ion-conductive elastomer (SF-supra-ICE) that eliminates the dehydration problem of hydrogels and possesses excellent biocompatibility, is reported. The SF-supra-ICE with high ionic conductivity (>3.3 × 10-2  S m-1 ) exhibits skin-like softness and strain-stiffening behaviors, excellent elasticity, breathability, and self-adhesiveness. Importantly, the SF-supra-ICE can be obtained by a simple water evaporation step to solidify the aqueous precursor into a solvent-free nature. Therefore, the aqueous precursor can act as inks to be painted and printed into customized ionic tattoos (I-tattoos) for the construction of multifunctional on-skin bioelectronics. The painted I-tattoos exhibit ultraconformal and seamless contact with human skin, enabling long-term and high-fidelity recording of various electrophysiological signals with extraordinary immunity to motion artifacts. Human-machine interactions are achieved by exploiting the painted I-tattoos to transmit the electrophysiological signals of human beings. Stretchable I-tattoo electrode arrays, manufactured by the printing method, are demonstrated for multichannel digital diagnosis of the health condition of human back muscles and spine.

Towards improving the accuracy of musculoskeletal simulation of dynamic three-dimensional spine rotations with optimizing model and algorithm

BACKGROUND

The accuracy of musculoskeletal simulations greatly relies on model structures and optimization algorithms. This study investigated the unclarified influence of accounting for several commonly-simplified different model components and optimization criteria on spinal musculoskeletal simulations.

METHODS

The study constructed a full-body musculoskeletal model with passive components of functional spinal units and spinal muscles subject-specifically refined. A muscle redundancy solver was built with 15 optimization criteria. Three-dimensional spine rotations and spinal muscle activities were measured using optical motion capture and electromyogram techniques when eight healthy volunteers performed standing, flexion/extension, lateral bending, and axial rotation. The effect of the model with four different conditions of the passive components and the sensitivity of the 15 optimization criteria on simulations were investigated.

RESULTS

Accounting for the refined passive components significantly improved the simulation accuracy. Different optimization criteria behaved distinctly for different motions. Generally minimizing the sum of squared muscle activations outperformed the others, with the highest averaged correlation coefficient (0.82) between the estimated erector spinae muscle activations and measured electromyography and with the estimated joint compression forces comparable to in vivo reference data.

CONCLUSION

This study highlights the importance of passive model components and proposes a suitable optimization framework for realistic spinal musculoskeletal simulations.