Analysis of inter-joint coordination during the sit-to-stand and stand-to-sit tasks in stroke patients with hemiplegia.

BACKGROUND: Inter-joint coordination is an important factor affecting postural stability, and its variability increases after fatigue. This study aimed to investigate the coordination pattern of lower limb joints during the sit-to-stand (Si-St) and stand-to-sit (St-Si) tasks in stroke patients and explore the influence of duration on inter-joint coordination. METHODS: Thirteen stroke hemiplegia patients (five with left paretic and eight right paretic) and thirteen age-matched healthy subjects were recruited. The Si-St and St-Si tasks were performed while each subject's joint kinematics were recorded using a three-dimensional motion capture system. Sagittal joint angles of the bilateral hip, knee and ankle joints as well as the movement duration were extracted. The angle-angle diagrams for the hip-knee, hip-ankle and knee-ankle joint were plotted to assess the inter-joint coordination. The inter-joint coordination was quantified using geometric characteristics of the angle-angle diagrams, including perimeter, area and dimensionless ratio. The coefficient of variation (CV) was performed to compare variability of the coordination parameters. RESULTS: There were no significant differences in the perimeter, area and dimensionless ratio values of the bilateral hip-knee, hip-ankle and knee-ankle inter-joints during Si-St and St-Si tasks in the stroke group. The perimeter values of bilateral hip-knee and knee-ankle inter-joints in the stroke group were lower (P<0.05) than in the healthy group during Si-St and St-Si tasks. Although no significant bilateral differences were found, the inter-joint coordination in stroke patients decreased with the increased movement duration of both Si-St and St-Si tasks. Additionally, the CV of the hip-knee inter-joint area during the Si-St task in the stroke group was less than (P<0.05) that in the healthy group. CONCLUSION: Stroke patients exhibit different inter-joint coordination patterns than healthy controls during the Si-St and St-Si tasks. The duration affects joint coordination, and inter-joint coordination is limited on the hemiplegic side joint pairs, which may lead to inconsistency in the rhythm of the left and right leg inter-joint movements and increase the risk of falls. These findings provide new insights into motor control rehabilitation strategies and may help planning targeted interventions for stoke patients with hemiplegia.

Quantitative assessment of spasticity: a narrative review of novel approaches and technologies.

Spasticity is a complex neurological disorder, causing significant physical disabilities and affecting patients' independence and quality of daily lives. Current spasticity assessment methods are questioned for their non-standardized measurement protocols, limited reliabilities, and capabilities in distinguishing neuron or non-neuron factors in upper motor neuron lesion. A series of new approaches are developed for improving the effectiveness of current clinical used spasticity assessment methods with the developing technology in biosensors, robotics, medical imaging, biomechanics, telemedicine, and artificial intelligence. We investigated the reliabilities and effectiveness of current spasticity measures employed in clinical environments and the newly developed approaches, published from 2016 to date, which have the potential to be used in clinical environments. The new spasticity scales, taking advantage of quantified information such as torque, or echo intensity, the velocity-dependent feature and patients' self-reported information, grade spasticity semi-quantitatively, have competitive or better reliability than previous spasticity scales. Medical imaging technologies, including near-infrared spectroscopy, magnetic resonance imaging, ultrasound and thermography, can measure muscle hemodynamics and metabolism, muscle tissue properties, or temperature of tissue. Medical imaging-based methods are feasible to provide quantitative information in assessing and monitoring muscle spasticity. Portable devices, robotic based equipment or myotonometry, using information from angular, inertial, torque or surface EMG sensors, can quantify spasticity with the help of machine learning algorithms. However, spasticity measures using those devices are normally not physiological sound. Repetitive peripheral magnetic stimulation can assess patients with severe spasticity, which lost voluntary contractions. Neuromusculoskeletal modeling evaluates the neural and non-neural properties and may gain insights into the underlying pathology of spasticity muscles. Telemedicine technology enables outpatient spasticity assessment. The newly developed spasticity methods aim to standardize experimental protocols and outcome measures and enable quantified, accurate, and intelligent assessment. However, more work is needed to investigate and improve the effectiveness and accuracy of spasticity assessment.