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

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.

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.