Lower Limb Movement Research Articles

Comparing the Effects of Three Methods of Foot Massage on Movement Performance, Risk of Falling, and Quality of Life (QoL) In Men With Blindness

Background and Aims Weakness in receptors involved in proprioception can limit the range of motion of the ankle and knee, as one of the most important causes of lower limb movement disorder and the risk of falling. People with sensory disorders such as visual impairment, have limitations in performing daily activities, and their physical activity, muscle strength, cardiovascular endurance, balance, and athletic performance decrease. This study aims to compare the effects of three foot massage techniques on movement performance, risk of falling, and quality of life of visually impaired men, and assess the persistence of their effects. Methods This is a quasi-experimental study with a pretest/posttest/follow-up design. Thirty men with blindness were randomly divided into three intervention groups including foot massage with a ball (n=10), foot massage with a brush (n=10), and foot massage with hands(n=10). They received foot massage for 21 days, massage day for 10 minutes (5 minutes for each foot). The Tinetti test was used to assess movement performance. The timed up & go test was used to measure the risk of falling, and the 36-item short form survey (SF-36) was used for evaluating the quality of life in the pretest, posttest, and follow-up (Short-term persistence) phases. One-way analysis of variance was used for between-group comparisons and repeated measures analysis of variance was used for within-group comparisons. Results There was no significant difference among groups in the quality of life and the risk of falling. There was a significant difference among them only in movement performance, where the group received foot massage with hands had higher performance. The results of repeated measures analysis of variance for the factor of time showed that the three methods improved movement performance, quality of life and reduced the risk of falling. All three methods had a significant effect on the study variables (P<0.05). Conclusion Three methods of foot massage have a significant effect on movement performance, risk of falling, and quality of life of men with blindness, by strengthening their proprioception receptors.

Event-Triggered Sliding Mode Impulsive Control for Lower Limb Rehabilitation Exoskeleton Robot Gait Tracking

Lower limb rehabilitation exoskeleton robots (LLRERs) play an important role in lower limb rehabilitation training and assistance walking for patients with lower limb movement disorders. In order to reduce and eliminate adverse effects on the accuracy of human motion gait tracking during walking with an LLRER, which is caused by the gravity and friction, the periodic ground shock force, and the human–exoskeleton interaction force, this paper proposes a feedforward–feedback hybrid control strategy of sliding mode impulsive control with gravity and friction compensation, based on the event-triggered mechanism of Lyapunov function. Firstly, to realize high-precision gait tracking with bounded error, some constraints on controller parameters are deduced by analyzing the Lyapunov-based stability. Secondly, the Zeno behavior of impulsive event triggers is excluded by the analysis of three different cases of the triggering time sequence. Finally, the effectiveness of the proposed hybrid controller is verified by the numerical simulation of the LLRER human–exoskeleton integrated system based on a three-link simplified model. It shows that an event-triggered sliding mode impulsive control strategy with gravity and friction compensation can achieve complete gait tracking with bounded error and has excellent dynamic performance under the constraints.

ViT-LLMR: Vision Transformer-based lower limb motion recognition from fusion signals of MMG and IMU

One of the key problems in lower limb-based human–computer interaction (HCI) technology is to use wearable devices to recognize the wearer's lower limb motions. The information commonly used to discriminate human motion mainly includes biological and kinematic signals. Considering that unimodal signals do not provide enough information to recognize lower limb movements, in this paper, we proposed a Vision Transformer (ViT)-based architecture for lower limb motion recognition from multichannel Mechanomyography (MMG) signals and kinematic data. Firstly, we applied the self-attention mechanism to enhance each input channel signal. Then the data was fed into ViT model. Vision Transformer-based Lower Limb Motion Recognition (ViT - LLMR) architecture proposed in this paper can avoid the model training problems such as autonomous feature extraction and feature selection for machine learning, and the model can recognize eight lower limb motions containing six subjects with an accuracy of 94.62%. In addition, we analyzed the generalization ability of the model when undersampling and only collecting fragment signals. In conclusion, the proposed ViT - LLMR architecture could provide a basis for practical applications in different HCI fields.

Brain Response Induced by Peroneal Electrical Transcutaneous Neuromodulation Invented for Overactive Bladder Treatment, as Detected by Functional Magnetic Resonance Imaging

ObjectivesIn this study, we aimed to investigate whether peroneal electrical Transcutaneous Neuromodulation invented for overactive bladder (OAB) treatment elicits activation in brain regions involved in neural regulation of the lower urinary tract. Materials and MethodsAmong 22 enrolled healthy female volunteers, 13 were eligible for the final analysis. Functional magnetic resonance imaging (fMRI) (Siemens VIDA 3T; Erlangen, Germany) was used to compare the brain region activation elicited by peroneal electrical Transcutaneous Neuromodulation with the activation elicited by sham stimulation. Each subject underwent brain fMRI recording during eight 30-second periods of rest, alternating with 30-second periods of passive feet movement using the sham device, mimicking the motor response to peroneal nerve stimulation. Subsequently, fMRI recording was performed during the analogic “off-on” stimulation paradigm using peroneal electrical transcutaneous neuromodulation. Magnetic resonance imaging data acquired during both paradigms were compared using individual and group statistics. ResultsDuring both peroneal electrical Transcutaneous Neuromodulation and sham feet movements, we observed activation of the primary motor cortex and supplementary motor area, corresponding to the cortical projection of lower limb movement. During peroneal electrical Transcutaneous Neuromodulation, we observed significant activations in the brain stem, cerebellum, cingulate gyrus, putamen, operculum, and anterior insula, which were not observed during the sham feet movement. ConclusionsOur study provides evidence that peroneal electrical Transcutaneous Neuromodulation elicits activation of brain structures that have been previously implicated in the perception of bladder fullness and that play a role in the ability to cope with urinary urgency. Our data suggest that neuromodulation at the level of supraspinal control of the lower urinary tract may contribute to the treatment effect of peroneal electrical Transcutaneous Neuromodulation in patients with OAB.

Criterion validity of neural networks to assess lower limb motion during cycling

ABSTRACT The use of marker-less methods to automatically obtain kinematics of movement is expanding but validity to high-velocity tasks such as cycling with the presence of the bicycle on the field of view is needed when standard video footage is obtained. The purpose of this study was to assess if pre-trained neural networks are valid for calculations of lower limb joint kinematics during cycling. Motion of twenty-six cyclists pedalling on a cycle trainer was captured by a video camera capturing frames from the sagittal plane whilst reflective markers were attached to their lower limb. The marker-tracking method was compared to two established deep learning-based approaches (Microsoft Research Asia-MSRA and OpenPose) to estimate hip, knee and ankle joint angles. Poor to moderate agreement was found for both methods, with OpenPose differing from the criterion by 4–8° for the hip and knee joints. Larger errors were observed for the ankle joint (15–22°) but no significant differences between methods throughout the crank cycle when assessed using Statistical Parametric Mapping were observed for any of the joints. OpenPose presented stronger agreement with marker-tracking (criterion) than the MSRA for the hip and knee joints but resulted in poor agreement for the ankle joint.

Lower Limb Motion Classification Using Energy Density Features of Surface Electromyography Signals’ Activation Region and Dynamic Ensemble Model

Accurate classification of lower-limb movements based on surface electromyography (sEMG) signals is vital for wearable auxiliary devices in military and medical rehabilitation. It is difficult to accurately obtain the effective features of the active region and establish a reliable classification model of complex lower-limb motion modes due to the strong dynamic time variability of the sEMG signals. Thus, an onset point detection algorithm, namely the maximum interclass variance (MIV) algorithm, was proposed to determine an accurate activation signal region. Then, a variational modal correlation dimension (VMCD) algorithm was proposed for feature construction to obtain the energy density feature (EDF) of the activation region, which reflects the activation signal’s amplitude energy distribution state. Finally, a random sampling multi-classifier dynamic ensemble (RSDE) algorithm was proposed to rapidly construct an ensemble model by adapting to the feature changes of the sEMG signals. A total of 25 subjects were recruited to participate in the experiment. Compared with the other methods, the proposed method could accurately classify five lower-limb motions by collecting only the data from three lower-limb muscles. The average accuracy and response time were better than those of many existing classification methods. This indicates that the proposed method can improve the man-machine cooperative response speed, which is beneficial to enhance the application effect of sEMG auxiliary equipment.

A Wearable Computer Vision System With Gimbal Enables Position-, Speed-, and Phase-Independent Terrain Classification for Lower Limb Prostheses.

Computer vision can provide upcoming walking environment information for lower limb-assisted robots, thereby enabling more accurate and robust decisions for high-level control. However, current computer vision systems in lower extremity devices are still constrained by the disruptions that occur in the interaction between human, machine, and the environment, which hinder optimal performance. In this paper, we propose a gimbal-based terrain classification system that can be adapted to different lower limb movements, different walking speeds, and gait phases. We use a linear active disturbance rejection controller to realize fast response and anti-disturbance control of the gimbal, which allows computer vision to continuously and stably focus on the desired field of view angle during lower limb motion interaction. We also deployed a lightweight MobileNetV2 model in an embedded vision module for real-time and highly accurate inference performance. By using the proposed terrain classification system, it can provide the ability to classify and predict terrain independent of mounting position (thighs and shanks), gait phase, and walking speed. This also makes our system applicable to subjects with different physical conditions (e.g., non-disabled subjects and individuals with transfemoral amputation) without tuning the parameters, which will contribute to the plug-and-play functionality of terrain classification. Finally, our approach is promising to improve the adaptability of lower limb assisted robots in complex terrain, allowing the wearer to walk more safely.

Static Standing Balance With Musculoskeletal Models Using PPO With Reward Shaping

The ability of the human body to maintain static standing balance is the basis for other lower limb movements. To compensate for the shortcomings of existing musculoskeletal model control methods in standing balance such as few degrees of freedom, short control time, and low simulation confidence, this paper proposes a method based on proximal policy optimization with reward shaping to achieve the balance task of human-like models. First, a reward function on pelvis velocity and muscle fatigue was defined according to the model features and moving target, and a proximal policy optimization with reward shaping was used to train the controller and finish the expected mission. Then, the kinematic and dynamic data of human static balance were collected, and the effectiveness of the method was verified by calculating and comparing the center of mass, ground reaction force, and joint angle in the agent and subjects. The results show that the agent swaying distance of the center of mass is smaller than the mean value of subjects, which is 0.4 mm and 2.6 mm shorter in the sagittal and coronal planes, respectively; the error between the agent ground reaction force and subjects is less than 0.03; and the joint angle of the agent were all within the range measured by the experiment. The method allows efficient and prolonged control of 3D lower limb musculoskeletal models, providing strong evidence for the feasibility of deep reinforcement learning techniques in synthesizing physiologically accurate movements.

Sciatica masquerading parathyroid carcinoma

Primary hyperparathyroidism is detected in the Western world in an asymptomatic stage due to routine calcium screening. In India, patients are still diagnosed with various symptoms such as bone disease and renal disease and only 5.6% are in the asymptomatic stage. A 48-year-old female came with complaints of right hip pain of 1-month duration. She had low back pain a year ago radiating to both thighs. The pain was not suggestive of inflammatory arthritis, and the autoimmune profile was negative. The pain progressively worsened, and the patient became bedridden. General examination revealed left-sided neck swelling that moved with deglutition. Right lower-limb movement was restricted by severe pain. Magnetic resonance imaging of the lumbar spine revealed a diffuse altered signal intensity involving the entire spine, bilateral pelvis, and femur with hypointense on both T1 and T2 images suggestive of marrow infiltrative disorder. Her serum calcium was 12.7 mg/dl and serum phosphorus was 1.9 mg/dl. The patient's alkaline phosphatase was 2919 IU/L. Her parathyroid hormone level was 2095 pg/ml. The patient was diagnosed to have hyperparathyroidism. 99mTc-sestamibi parathyroid single-photon emission computed tomography–computed tomography was suggestive of left superior parathyroid adenoma. The surgical endocrinologist did a left superior parathyroidectomy. Postoperatively, she developed hypocalcemia. It was managed with intravenous calcium infusion, oral calcium, and oral calcitriol. Six weeks after surgery, the pain in the right hip decreased significantly, and she was able to walk without support. Histopathological examination of the removed parathyroid was suggestive of parathyroid carcinoma. The following core competencies are addressed in this article: Practice-based learning and improvement, Medical knowledge.

Lower-limb sagittal joint angles during gait can be predicted based on foot acceleration and angular velocity.

Continuous monitoring of lower-limb movement may help in the early detection and control/reduction of diseases (such as the progression of orthopedic diseases) by applying suitable interventions. Therefore, it is invaluable to calculate the lower-limb movement (sagittal joint angles) while walking daily for continuous evaluation of such risks. Although cameras in a motion capture system are necessary for calculating lower-limb sagittal joint angles during gait, the method is unrealistic considering the setting is difficult to achieve in daily life. Therefore, the estimation of lower-limb sagittal joint angles during walking based on variables, which can be measured using wearable sensors (e.g., foot acceleration and angular velocity), is important. This study estimates the lower-limb sagittal joint angles during gait from the norms of foot acceleration and angular velocity using machine learning and validates the accuracy of the estimated joint angles with those obtained using a motion capture system. Healthy adults (n = 200) were asked to walk at a comfortable speed (10 trials), and their lower-limb sagittal joint angles, foot accelerations, and angular velocities were obtained. Using these variables, we established a feedforward neural network and estimated the lower-limb sagittal joint angles. The average root mean squared errors of the lower-limb sagittal joint angles during gait ranged between 2.5°-7.0° (hip: 7.0°; knee: 4.0°; and ankle: 2.5°). These results show that we can estimate the lower-limb sagittal joint angles during gait using only the norms of foot acceleration and angular velocity, which can help calculate the lower-limb sagittal joint angles during daily walking.

Kinematic analysis and development of cable-driven rehabilitation robot for cerebral palsy patients

This study aimed to analyze the kinematic development of a rehabilitation cable robot for patients with cerebral palsy problems. For this purpose, the walking pattern of a healthy person was analyzed in the robot by extracting his kinematic model. Therefore, a seven-link model was considered, and changes in the mass center of the links and then movements during the gait cycle were obtained with the angles related to joint changes. Next, the person’s integration with the rehabilitation cable robot was investigated with the resolution of the direct kinematic problem. In addition, the change-related outputs of the cables were obtained by the person’s movement and the attached belt. The robot was further proposed because the specific change diagram of the cables facilitates understanding how much motor torque is needed to change the length of the cable. It is noteworthy that the static person balance is provided in the existing rehabilitation robots. However, in this structure, the balance is done by the six degrees of freedom robot so that the robot can return the person to the original path when he loses his balance. Cable systems for the lower limbs (thighs and shanks) are also simulated to rehabilitate the patient. The obtained results from the simulation and the obtained output from kinematic equations for lower limb movements were also compared, and the highest deference was 2.2, 1.8, 1.8, and 1.5% for shank-back, shank-front, thigh-back, and thigh-front of the leg in the corresponding points in the outputs of both software, respectively.

ANÁLISE CINEMÁTICA DAS TÉCNICAS DE MOVIMENTO DOS MEMBROS INFERIORES NO TREINAMENTO DE FUTEBOL

ABSTRACT Introduction The improvement of soccer sports skills depends on many training efforts and is closely related to intrinsic scientific methods. Attention to the integral quality of the lower limb muscles and the performance of specific exercises of technical movements is essential to reach the optimal state of physical performance in players. Objective Analyze the kinematic effect of lower limb movement techniques in soccer training. Methods 10 athletes were marked with reflective spheres and submitted to the kinematic training method of the lower limbs designed by the coaches in 60 minutes, three times a week, for six weeks. Before and after the experiment, data captured by reflective spheres were captured, compared, classified, and analyzed. Results Kinematic training can effectively optimize movement time, swing amplitude, swing angle, and other aspects of lower limb mechanical structure, thus improving energy expenditure and making the movement concise, conveying strength and precision. Conclusion Trainers should seriously study the principles of applied kinematic analysis and optimize the training program from a scientific point of view because the athletic level of athletes is significantly improved with this real-time feedback. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

Imaging the lower limb network in Parkinson’s disease

BackgroundDespite the significant impact of lower limb symptoms on everyday life activities in Parkinson’s disease (PD), knowledge of the neural correlates of lower limb deficits is limited. ObjectiveWe ran an fMRI study to investigate the neural correlates of lower limb movements in individuals with and without PD. MethodsParticipants included 24 PD and 21 older adults who were scanned while performing a precisely controlled isometric force generation task by dorsiflexing their ankle. A novel MRI-compatible ankle dorsiflexion device that limits head motion during motor tasks was used. The PD were tested on their more affected side, whereas the side in controls was randomized. Importantly, PD were tested in the off-state, following overnight withdrawal from antiparkinsonian medication. ResultsThe foot task revealed extensive functional brain changes in PD compared to controls, with reduced fMRI signal during ankle dorsiflexion within the contralateral putamen and M1 foot area, and ipsilateral cerebellum. The activity of M1 foot area was negatively correlated with the severity of foot symptoms based on the Movement Disorder Society‐Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS-III). ConclusionOverall, current findings provide new evidence of brain changes underlying motor symptoms in PD. Our results suggest that pathophysiology of lower limb symptoms in PD appears to involve both the cortico-basal ganglia and cortico-cerebellar motor circuits.

Effect of one hour kick boxing exercise on lipid profile

Background: Physical inactivity and a sedentary lifestyle are contributory factors for increased risk of obesity, hypertension, hyperlipidemia, and related complications, namely cardiovascular diseases. Cardiovascular diseases, namely atherosclerosis, myocardial infarction, and stroke are very common cardiovascular complications of uncontrolled hyperlipidemia. On the other hand, regular physical exercise decreases weight and body fat deposits. Regular exercise also increases high-density lipoprotein (HDL) cholesterol and therefore decreases the risk of atherosclerosis. Different studies on the effects of acute one session of exercise on lipid profile have shown variable results. Our study aimed to study effects of 1 h intensive exercise on the lipid profile of females performing regular exercise for 1 year. The lipid profile study included total cholesterol (TC), triglycerides (TG), low-density cholesterol low-density lipoprotein (LDL), Very low-density lipoproteins (VLDL), and HDL cholesterol. Aims and Objectives: (1) To compare blood levels of TC and TG before exercise and immediately after 1 h exercise (2) To compare blood levels of HDL, LDL, and VLDL before exercise and immediately after 1 h exercise. Materials and Methods: The study included 30 females in the age group of 20–50 years. Exercise included warming up for 10 min, followed by intense exercise for 40 min and then the last 10 min of relaxing exercise. Kickboxing exercise included upper limb and lower limb movements mimicking punching. Blood samples were collected from the antecubital vein with all aseptic precautions. Two blood samples were collected. First sample before the exercise and the second sample was immediately after 1 h of intense exercise. 2 mL blood was collected in a container without any anticoagulant. A lipid profile study for TC, TG, HDL, LDL, and VLDL was done using the automated biochemical analyzer. Results: In our study, the post exercise samples showed a significant increase in HDL levels and significantly decreased levels of TC, TG, LDL and VLDL. Conclusion: The effects of one session of intense exercise on lipid profile in females are beneficial as HDL levels are increased and TG, LDL and VLDL levels are decreased. These results are encouraging and useful for promoting females for regular exercise. This is very important for perimenopausal and postmenopausal females, as after menopause females are more prone for hypercholesterolemia due to a lack of estrogen.

Impact of the Interdisciplinary Chronic Pain Rehabilitation Programme in patients with and without sleep disorders

Sleep disorders and chronic pain are linked to each other bidirectionally. Both are related to affective disorders, fatigue, depression, anxiety and drug abuse, and have a significant effect on quality of life. The Interdisciplinary Pain Programme (IDP) aims to relieve the patients' pain and improve their functionality by incorporating healthy postural, sleep and nutritional habits, relaxation techniques, physical exercise and cognitive-behavioural mechanisms. A retrospective, observational, cross-sectional study was conducted. A total of 323 patients with chronic pain who completed the IDP were examined. They were assessed at the beginning and at the end of the programme with pain, depression, quality of life and insomnia scales, and were then compared between groups with and without insomnia, that is, with an insomnia severity index (ISI) less than 15 versus greater than or equal to 15. Fifty-eight patients were studied by means of polysomnography. A significant improvement (p < 0.0001) in pain, depression and quality of life, as assessed by the visual analogue scale (VAS), the Beck inventory and the Short Form-36 (SF-36) questionnaire was observed in chronic pain patients with an ISI below 15 and in those with an ISI greater than or equal to 15. The results were superior in the group of patients with insomnia. The presence of a high apnoea and hypopnoea index and periodic lower limb movements in patients was not related to improvements on the Beck, SF-36, ISI and VAS scales. In conclusion, IDP benefits patients with chronic non-cancer-induced pain in several affected areas, in addition to pain, due to a comprehensive treatment. Polysomnography can help diagnose specific pathologies and individualise pharmacological treatment.

A gait stability evaluation method based on wearable acceleration sensors.

In this study, an accurate tool is provided for the evaluation of the effect of joint motion effect on gait stability. This quantitative gait evaluation method relies exclusively on the analysis of data acquired using acceleration sensors. First, the acceleration signal of lower limb motion is collected dynamically in real-time through the acceleration sensor. Second, an algorithm based on improved dynamic time warping (DTW) is proposed and used to calculate the gait stability index of the lower limbs. Finally, the effects of different joint braces on gait stability are analyzed. The experimental results show that the joint brace at the ankle and the knee reduces the range of motions of both ankle and knee joints, and a certain impact is exerted on the gait stability. In comparison to the ankle joint brace, the knee joint brace inflicts increased disturbance on the gait stability. Compared to the joint motion of the braced side, which showed a large deviation, the joint motion of the unbraced side was more similar to that of the normal walking process. In this paper, the quantitative evaluation algorithm based on DTW makes the results more intuitive and has potential application value in the evaluation of lower limb dysfunction, clinical training and rehabilitation.

Machine Learning Based Recognition of Elements in Lower-Limb Movement Sequence for Proactive Control of Exoskeletons to Assist Lifting

Machine Learning Based Recognition of Elements in Lower-Limb Movement Sequence for Proactive Control of Exoskeletons to Assist Lifting

Robust Cadence and Power Tracking on a Switched FES Cycle With an Unknown Electromechanical Delay

Functional electrical stimulation (FES) is commonly used to facilitate cycling tasks for people with lower-limb movement disorders. In this work, FES and motor controllers are designed to track a desired power and cadence, respectively, and a Lyapunov-based switched systems analysis is performed to guarantee uniformly ultimately bounded power tracking and global exponential cadence tracking for a switched, delayed, nonlinear, and uncertain FES-cycling system. A unique challenge in this problem is that there is an unknown time-varying input delay to produce force, and a different unknown time-varying residual input delay where force is still produced after stimulation is removed. These delays impact the dwell-time conditions that dictate stimulation timing, and if not properly accounted for can lead to undesired effects such as antagonistic muscles exerting force at the same time or potential instabilities. The proposed controllers were validated by experimental analysis of four participants with neurological conditions (NCs) and five able-bodied participants, and yielded average power and cadence tracking errors of 0.01 ± 0.09 W and −0.05 ± 0.65 revolutions per minute (RPM), respectively, for the able-bodied participants and 0.01 ± 1.11 W and −0.07 ± 1.17 RPM, respectively, for the participants with NCs.

A Novel Lower-Limb Coordination Assessment Scheme Using Multi-Scale Nonlinear Coupling Characteristics With sEMG

Motor dysfunction (e.g., incoordination of upper or lower limb) significantly limits the individuals’ ability of daily living, and thus the provisioning of a motion coordination assessment method becomes of vital importance. As a quantitative indicator, inter-muscular coupling strength could assess limb coordination. Since surface electromyography (sEMG) signals cover nonlinear coupling characteristics, in this paper, a lower-limb motion coordination assessment scheme with intermuscular coherence (IMC) analysis and optimization variational mode decomposition (VMD) is proposed. First, sEMG signals are decomposed into several intrinsic mode functions (IMFs) using optimized VMD. Then, the nonlinear coupling feature vector in the beta-band frequency domian (15-35Hz) is extracted by the G-P algorithm from optimal IMF, thereby estimating intermuscular coupling strength by IMC. In particular, differential evolution (DE) algorithm’s global optimization capability and envelope entropy (EE)’s sparsity are adopted to provide the basis for optimization VMD and screening optimal IMF, respectively. Finally, signals are collected from four muscle pairs of the 12 male and 12 female subjects to assess lower-limb motions coordination. Simultaneously, the independent sample T test is leveraged to compare the effects of gender on groups’ characteristics (e.g., age, height, and body mass). Results demonstrate not only the effectiveness of the proposed approach (i.e., p < 0.01 with both “S-walking” and “Running” motions, p < 0.05 with “Q-walking”), but also the difference of motion coordination relationship between male and female adults as well as the significance of muscle selection.

Diabetic striatopathy: An uncommon complication of diabetes mellitus

Diabetic striatopathy is an uncommon neurological manifestation of hyperosmolar hyperglycemic syndrome. A case of a 74-year-old woman is presented here. She presented with abnormal movements of left upper and lower limbs and was found to have high index blood sugar. Non contrast CT brain showed hyperdense area in right striatal region. Based on clinical presentation, high blood sugar and radiological finding, she was diagnosed with diabetic striatopathy. The radiological abnormality and the symptoms improved rapidly and remarkably with strict glycaemic control.