Association between sleep patterns and galectin-3 in a Chinese community population.

BACKGROUND: Irregular sleep patterns have been associated with inflammation. Galectin-3, a novel biomarker, plays an important role in inflammation. We investigated the relationship between sleep patterns and galectin-3 in a Chinese population. METHODS: A total of 1,058 participants from the Shenzhen-Hong Kong United Network on Cardiovascular Disease study were included in the analysis. Age and sex-adjusted linear regression models were employed to investigate the relationship between galectin-3 level and traditional metabolic biomarkers. Logistic regression models were used to estimate the association among sleep disturbance, nighttime sleep duration, and daytime napping duration and elevated galectin-3, with elevated galectin-3 defined as galectin-3 level > 65.1 ng/ml. RESULTS: Of study participants, the mean age was 45.3 years and 54.3% were women. Waist circumference, natural logarithm (ln)-transformed triglyceride, and ln-transformed high sensitivity C-reactive protein were positively associated with galectin-3 level (age and sex-adjusted standardized ß [95% confidence interval (CI)], 0.12 [0.04, 0.21], 0.11 [0.05, 0.17], and 0.08 [0.02, 0.14], respectively). Sleep disturbance was associated with elevated galectin-3 (odds ratio [95% CI], 1.68 [1.05, 2.68], compared to those without sleep disturbance) after adjusting for traditional metabolic biomarkers. No interaction was observed between galectin-3 and age, sex, obesity, hypertension, and diabetes on sleep disturbance. No association was found between nighttime sleep duration or daytime napping duration and elevated galectin-3. CONCLUSIONS: Our study provides evidence of a significant association between sleep disturbance and elevated galectin-3 level, independent of traditional metabolic biomarkers. Screening and interventions on galectin-3 could assist in preventing sleep disturbance-induced inflammatory disease.

Impact of healthy lifestyles on risk of hypertension in the Chinese population: finding from SHUN-CVD study.

INTRODUCTION: Lifestyle factors are known to play a role in the development of hypertension. We aimed to study the relationship between lifestyle and hypertension in a Chinese population. METHODS: This study involved 3,329 participants (1,463 men and 1,866 women) aged 18-96 years in the Shenzhen-Hong Kong United Network on Cardiovascular Disease. A healthy lifestyle score was derived from 5 factors: no smoking, no alcohol consumption, active physical activity, normal body mass index, and a healthy diet. Multiple logistic regression was used to investigate the relationship between lifestyle score and hypertension. The influence of each lifestyle component on hypertension was also assessed. RESULTS: In the overall population, 950 (28.5%) participants had hypertension. The risk of hypertension decreased with increasing healthy lifestyle scores. Compared with participants with the lowest score (score: 0), the multivariable odds ratios (ORs) and corresponding 95% confidence intervals for participants with scores 3, 4, and 5 were 0.65 (0.41-1.01), 0.62 (0.40-0.97), and 0.37 (0.22-0.61), respectively (P for trend <0.001). After adjusting for age, sex, and diabetes, the score was associated with hypertension risk (P for trend = 0.005). Compared with a lifestyle score of 0, the adjusted OR for hypertension for participants with a score of 5 was 0.46 (0.26-0.80). CONCLUSIONS: The risk of hypertension is inversely related to the healthy lifestyle score. This reinforces the need to address lifestyle to reduce the risk of hypertension.

Feature Selection and Predictors of Falls with Foot Force Sensors Using KNN-Based Algorithms.

The aging process may lead to the degradation of lower extremity function in the elderly population, which can restrict their daily quality of life and gradually increase the fall risk. We aimed to determine whether objective measures of physical function could predict subsequent falls. Ground reaction force (GRF) data, which was quantified by sample entropy, was collected by foot force sensors. Thirty eight subjects (23 fallers and 15 non-fallers) participated in functional movement tests, including walking and sit-to-stand (STS). A feature selection algorithm was used to select relevant features to classify the elderly into two groups: at risk and not at risk of falling down, for three KNN-based classifiers: local mean-based k-nearest neighbor (LMKNN), pseudo nearest neighbor (PNN), local mean pseudo nearest neighbor (LMPNN) classification. We compared classification performances, and achieved the best results with LMPNN, with sensitivity, specificity and accuracy all 100%. Moreover, a subset of GRFs was significantly different between the two groups via Wilcoxon rank sum test, which is compatible with the classification results. This method could potentially be used by non-experts to monitor balance and the risk of falling down in the elderly population.

Relationship of EMG/SMG features and muscle strength level: an exploratory study on tibialis anterior muscles during plantar-flexion among hemiplegia patients.

BACKGROUND: Improvement in muscle strength is an important aim for the rehabilitation of hemiplegia patients. Presently, the rehabilitation prescription depends on the evaluation results of muscle strength, which are routinely estimated by experienced physicians and therefore not finely quantitative. Widely-used quantification methods for disability, such as Barthel Index (BI) and motor component of Functional Independent Measure (M-FIM), yet have limitations in their application, since both of them differentiated disability better in lower than higher disability, and they are subjective and recorded in wide scales. In this paper, to explore finely quantitative measures for evaluation of muscle strength level (MSL), we start with the study on quantified electromyography (EMG) and sonomyography (SMG) features of tibialis anterior (TA) muscles among hemiplegia patients. METHODS: 12 hemiplegia subjects volunteered to perform several sets of plantar-flexion movements in the study, and their EMG signals and SMG signals were recorded on TA independently to avoid interference. EMG data were filtered and then the root-mean-square (RMS) was computed. SMG signals, specifically speaking, the muscle thickness of TA, were manually measured by two experienced operators using ultrasonography. Reproducibility of the SMG assessment on TA between operators was evaluated by non-parametric test (independent sample T test). Possible relationship between muscle thickness changes (TC) of TA and muscle strength level of hemiplegia patients was estimated. RESULTS: Mean of EMG RMS between subjects is found linearly correlated with MSL (R2 = 0.903). And mean of TA muscle TC amplitudes is also linearly correlated with MSL among dysfunctional legs (R2 = 0.949). Moreover, rectified TC amplitudes (dysfunctional leg/ healthy leg, DLHL) and rectified EMG signals (DLHL) are found in linear correlation with MSL, with R2 = 0.756 and R2 = 0.676 respectively. Meanwhile, the preliminary results demonstrate that patients' peak values of TC are generally proportional to their personal EMG peak values in 12 dysfunctional legs and 12 healthy legs (R2 = 0.521). CONCLUSIONS: It's concluded that SMG could be a promising option to quantitatively estimate MSL for hemiplegia patients during rehabilitation besides EMG. However, after this exploratory study, they should be further investigated on a larger number of subjects.

Determination of acquisition frequency for intrafractional motion of pancreas in CyberKnife radiotherapy.

PURPOSE: To report the characteristics of pancreas motion as tracked using implanted fiducials during radiotherapy treatments with CyberKnife. METHODS AND MATERIALS: Twenty-nine patients with pancreas cancer treated using CyberKnife system were retrospectively selected for this study. During the treatment, the deviation is examined every 3-4 nodes (~45 s interval) and compensated by the robot. The pancreas displacement calculated from X-ray images acquired within the time interval between two consecutive couch motions constitute a data set. RESULTS: A total of 498 data sets and 4302 time stamps of X-ray images were analyzed in this study. The average duration for each data set is 634 s. The location of the pancreas becomes more dispersed as the time elapses. The acquisition frequency depends on the prespecified movement distance threshold of pancreas. If the threshold between two consecutive images is 1 mm, the acquisition frequency should be less than 30 s, while if the threshold is 2 mm, the acquisition frequency can be around 1 min. CONCLUSIONS: The pancreas target moves significantly and unpredictably during treatment. Effective means of compensating the intrafractional movement is critical to ensure adequate dose coverage of the tumor target.

Balance and knee extensibility evaluation of hemiplegic gait using an inertial body sensor network.

BACKGROUND: Most hemiplegic patients have difficulties in their balance and posture control while walking because of the asymmetrical posture and the abnormal body balance. The assessment of rehabilitation of hemiplegic gait is usually made by doctors using clinical scale, but it is difficult and could not be used frequently. It is therefore needed to quantitatively analyze the characteristics of hemiplegic gait. Thus the assessment would be simple, and real-time evaluation of rehabilitation could be carried out. METHODS: Twenty subjects (ten hemiplegic patients, ten normal subjects) were recruited. The subjects walked straight for five meters at their self-selected comfortable speed towards a target line on the floor.Xsens MTx motion trackers were used for acquiring gestures of body segments to estimate knee joint angles and identify gait cycles. A practical method for data acquisition that does not need to obtain accurate distances between a knee joint and its corresponding sensors is presented. RESULTS: The results showed that there were significant differences between the two groups in the three nominated angle amplitudes. The mean values of balance level of each parameter in hemiplegic gait and normal gait were: 0.21 versus 0.01, 0.18 versus 0.03, and 0.92 versus 0.03, respectively. The mean values of added angles of each parameter in hemiplegic gait and normal gait were: 74.64 versus 91.31, -76.48 versus -132.4, and 6.77 versus 35.74. CONCLUSIONS: It was concluded that the wearable bio-motion acquisition platform provided a practical approach that was effective in discriminating gait symptoms between hemiplegic and asymptomatic subjects. The extensibility of hemiplegic patients' lower limbs was significantly lower than that of normal subjects, and the hemiplegic gait had worse balance level compared with normal gait. The effect of rehabilitation training of hemiplegic gait could be quantitatively analyzed.

Sample entropy characteristics of movement for four foot types based on plantar centre of pressure during stance phase.

BACKGROUND: Motion characteristics of CoP (Centre of Pressure, the point of application of the resultant ground reaction force acting on the plate) are useful for foot type characteristics detection. To date, only few studies have investigated the nonlinear characteristics of CoP velocity and acceleration during the stance phase. The aim of this study is to investigate whether CoP regularity is different among four foot types (normal foot, pes valgus, hallux valgus and pes cavus); this might be useful for classification and diagnosis of foot injuries and diseases. To meet this goal, sample entropy, a measure of time-series regularity, was used to quantify the CoP regularity of four foot types. METHODS: One hundred and sixty five subjects that had the same foot type bilaterally (48 subjects with healthy feet, 22 with pes valgus, 47 with hallux valgus, and 48 with pes cavus) were recruited for this study. A Footscan® system was used to collect CoP data when each subject walked at normal and steady speed. The velocity and acceleration in medial-lateral (ML) and anterior-posterior (AP) directions, and resultant velocity and acceleration were derived from CoP. The sample entropy is the negative natural logarithm of the conditional probability that a subseries of length m that matches pointwise within a tolerance r also matches at the next point. This was used to quantify variables of CoP velocity and acceleration of four foot types. The parameters r (the tolerance) and m (the matching length) for sample entropy calculation have been determined by an optimal method. RESULTS: It has been found that in order to analyze all CoP parameters of velocity and acceleration during the stance phase of walking gait, for each variable there is a different optimal r value. On the contrary, the value m=4 is optimal for all variables.Sample entropies of both velocity and acceleration in AP direction were highly correlated with their corresponding resultant variables for r>0.91. The sample entropy of the velocity in AP direction was moderately correlated with the one of the acceleration in the same direction (r≥0.673), as well as with the resultant acceleration (r≥0.660). The sample entropy of resultant velocity was moderately correlated with the one of the acceleration in AP direction, as well as with the resultant acceleration (for the both r≥0.689). Moderate correlations were found between variables for the left foot and their corresponding variables for the right foot.Sample entropies of AP velocity, resultant velocity, AP acceleration, and resultant acceleration of the right foot as well as AP velocity and resultant velocity of the left foot were, respectively, significantly different among the four foot types. CONCLUSIONS: It can be concluded that the sample entropy of AP velocity (or the resultant velocity) of the left foot, ML velocity, resultant velocity, ML acceleration and resultant acceleration could serve for evaluation of foot types or selection of appropriate footwear.

A Precise Hip Protection System with Multi-scale Fall Warning Algorithm Based on Offset Displacement.

Falls occur frequently in daily life and the damage to the body is irreversible. Therefore, it is crucial to implement timely and effective warning and protection systems for falls to minimize the damage caused by falls. Currently, the fall warning algorithm has shortcomings such as low recognition rates for falls and fall-risk movements and insufficient lead-time, the time before the subject impacts the floor, making it difficult for falling protection devices to function effectively. In this study, a multi-scale falls warning algorithm based on offset displacement is built, and a hip protection system is designed. The performance of the algorithm and the system is validated using 150 falling and 500 fall-risk actions from 10 volunteers. The results showed that the recognition accuracy for falling actions is 98.7% and the recognition accuracy for fall-risk actions is 99.4%, with an average lead-time of 402ms. The protection rate for falling movements reached 98.7%. This proposed algorithm and hip protection system have the potential to be applied in elderly communities, hospitals, and homes to reduce the damage caused by falls.Clinical Relevance- This study provides important reference for clinicians in analyzing fall behaviors to patients at risk of falls in clinical settings, offering valuable technical support for ensuring the safety of patients in danger of falling. It also contributes to further promoting the development of falling-prevention medical devices.

A fuzzy granular logistic regression algorithm for sEMG-based cross-individual prosthetic hand gesture classification.

Objective.Prosthetic systems are used to improve the quality of life of post-amputation patients, and research on surface electromyography (sEMG)-based gesture classification has yielded rich results. Nonetheless, current gesture classification algorithms focus on the same subject, and cross-individual classification studies that overcome physiological factors are relatively scarce, resulting in a high abandonment rate for clinical prosthetic systems. The purpose of this research is to propose an algorithm that can significantly improve the accuracy of gesture classification across individuals.Approach.Eight healthy adults were recruited, and sEMG data of seven daily gestures were recorded. A modified fuzzy granularized logistic regression (FG_LogR) algorithm is proposed for cross-individual gesture classification.Main results.The results show that the average classification accuracy of the four features based on the FG_LogR algorithm is 79.7%, 83.6%, 79.0%, and 86.1%, while the classification accuracy based on the logistic regression algorithm is 76.2%, 79.5%, 71.1%, and 81.3%, the overall accuracy improved ranging from 3.5% to 7.9%. The performance of the FG_LogR algorithm is also superior to the other five classic algorithms, and the average prediction accuracy has increased by more than 5%.Conclusion. The proposed FG_LogR algorithm improves the accuracy of cross-individual gesture recognition by fuzzy and granulating the features, and has the potential for clinical application.Significance. The proposed algorithm in this study is expected to be combined with other feature optimization methods to achieve more precise and intelligent prosthetic control and solve the problems of poor gesture recognition and high abandonment rate of prosthetic systems.

Effective evaluation of HGcnMLP method for markerless 3D pose estimation of musculoskeletal diseases patients based on smartphone monocular video.

Markerless pose estimation based on computer vision provides a simpler and cheaper alternative to human motion capture, with great potential for clinical diagnosis and remote rehabilitation assessment. Currently, the markerless 3D pose estimation is mainly based on multi-view technology, while the more promising single-view technology has defects such as low accuracy and reliability, which seriously limits clinical application. This study proposes a high-resolution graph convolutional multilayer perception (HGcnMLP) human 3D pose estimation framework for smartphone monocular videos and estimates 15 healthy adults and 12 patients with musculoskeletal disorders (sarcopenia and osteoarthritis) gait spatiotemporal, knee angle, and center-of-mass (COM) velocity parameters, etc., and compared with the VICON gold standard system. The results show that most of the calculated parameters have excellent reliability (VICON, ICC (2, k): 0.853-0.982; Phone, ICC (2, k): 0.839-0.975) and validity (Pearson r: 0.808-0.978, p<0.05). In addition, the proposed system can better evaluate human gait balance ability, and the K-means++ clustering algorithm can successfully distinguish patients into different recovery level groups. This study verifies the potential of a single smartphone video for 3D human pose estimation for rehabilitation auxiliary diagnosis and balance level recognition, and is an effective attempt at the clinical application of emerging computer vision technology. In the future, it is hoped that the corresponding smartphone program will be developed to provide a low-cost, effective, and simple new tool for remote monitoring and rehabilitation assessment of patients.

Association of beta-2-microglobulin, cystatin C and lipocalin-2 with stroke risk in the general Chinese population.

INTRODUCTION: Beta-2-microglobulin (B2M), cystatin C and lipocalin-2 (LCN-2) are established renal biomarkers, yet their roles in stroke have not been fully evaluated. We aimed to investigate the relationship of B2M, cystatin C, and LCN-2 with stroke risk in a general Chinese population. METHODS: We used ordinal regression to study the relationship between serum B2M, cystatin C, and LCN-2 with stroke risk in 1060 participants (mean age 45.4 ± 10.8 years, 46% male) from the Shenzhen-Hong Kong United Network on Cardiovascular Disease (SHUN-CVD) study. Stroke risk was classified into low-risk, middle-risk and high-risk groups according to the China National Stroke Screening Survey criteria. Serum biomarker levels were measured using immunoturbidimetric assays. Participants with valid data on serum biomarker levels and stroke risk were included in the analysis. RESULTS: The number of participants in the low-risk, middle-risk and high-risk stroke risk groups were 663, 143 and 254 respectively. Elevated serum B2M, cystatin C, and LCN-2 levels were associated with being male, overweight/obesity, hypertension, alcohol consumption and smoking. Serum B2M, cystatin C and LCN-2 levels were significantly associated with stroke risk in the overall population (B2M: ß = 0.595, p < .001; cystatin C: ß = 3.718, p < .001; LCN-2: ß = 0.564, p < .001) after adjustment for age. CONCLUSION: Elevated serum B2M, cystatin C and LCN-2 levels are associated with stroke risk. They may be novel biomarkers for clinicians to assess stroke risk.Key messagesSerum beta-2-microglobulin, cystatin C and lipocalin-2 levels are significantly associated with stroke risk.Beta-2-microglobulin, cystatin C and lipocalin-2 may serve as useful biomarkers for stroke risk stratification in the general population.

Exploration and implementation of a pre-impact fall recognition method based on an inertial body sensor network.

The unintentional injuries due to falls in elderly people give rise to a multitude of health and economic problems due to the growing aging population. The use of early pre-impact fall alarm and self-protective control could greatly reduce fall injuries. This paper aimed to explore and implement a pre-impact fall recognition/alarm method for free-direction fall activities based on understanding of the pre-impact lead time of falls and the angle of body postural stability using an inertial body sensor network. Eight healthy Asian adult subjects were arranged to perform three kinds of daily living activities and three kinds of fall activities. Nine MTx sensor modules were used to measure the body segmental kinematic characteristics of each subject for pre-impact fall recognition/alarm. Our analysis of the kinematic features of human body segments showed that the chest was the optimal sensor placement for an early pre-impact recognition/alarm (i.e., prediction/alarm of a fall event before it happens) and post-fall detection (i.e., detection of a fall event after it already happened). Furthermore, by comparative analysis of threshold levels for acceleration and angular rate, two acceleration thresholds were determined for early pre-impact alarm (7 m/s/s) and post-fall detection (20 m/s/s) under experimental conditions. The critical angles of postural stability of torso segment in three kinds of fall activities (forward, sideway and backward fall) were determined as 23.9 ± 3.3, 49.9 ± 4.1 and 9.9 ± 2.5 degrees, respectively, and the relative average pre-impact lead times were 329 ± 21, 265 ± 35 and 257 ± 36 ms. The results implied that among the three fall activities the sideway fall was associated with the largest postural stability angle and the forward fall was associated with the longest time to adjust body angle to avoid the fall; the backward fall was the most difficult to avoid among the three kinds of fall events due to the toughest combination of shortest lead time and smallest angle of postural stability which made it difficult for the self-protective control mechanism to adjust the body in time to avoid falling down.

A low-cost body inertial-sensing network for practical gait discrimination of hemiplegia patients.

Gait analysis is widely used in detecting human walking disorders. Current gait analysis methods like video- or optical-based systems are expensive and cause invasion of human privacy. This article presents a self-developed low-cost body inertial-sensing network, which contains a base station, three wearable inertial measurement nodes, and the affiliated wireless communication protocol, for practical gait discrimination between hemiplegia patients and asymptomatic subjects. Every sensing node contains one three-axis accelerometer, one three-axis magnetometer, and one three-axis gyroscope. Seven hemiplegia patients (all were abnormal on the right side) and 7 asymptomatic subjects were examined. The three measurement nodes were attached on the thigh, the shank, and the dorsum of the foot, respectively (all on the right side of the body). A new method, which does not need to obtain accurate positions of the sensors, was used to calculate angles of knee flexion/extension and foot in the gait cycle. The angle amplitudes of initial contact, toe off, and knee flexion/extension were extracted. The results showed that there were significant differences between the two groups in the three angle amplitudes examined (-0.52±0.98° versus 6.94±2.63°, 28.33±11.66° versus 47.34±7.90°, and 26.85±8.6° versus 50.91±6.60°, respectively). It was concluded that the body inertial-sensing network platform provided a practical approach for wearable biomotion acquisition and was effective for discriminating gait symptoms between hemiplegia and asymptomatic subjects.

The reliability and validity of gait analysis system using 3D markerless pose estimation algorithms.

Quantifying kinematic gait for elderly people is a key factor for consideration in evaluating their overall health. However, gait analysis is often performed in the laboratory using optical sensors combined with reflective markers, which may delay the detection of health problems. This study aims to develop a 3D markerless pose estimation system using OpenPose and 3DPoseNet algorithms. Moreover, 30 participants performed a walking task. Sample entropy was adopted to study dynamic signal irregularity degree for gait parameters. Paired-sample t-test and intra-class correlation coefficients were used to assess validity and reliability. Furthermore, the agreement between the data obtained by markerless and marker-based measurements was assessed by Bland-Altman analysis. ICC (C, 1) indicated the test-retest reliability within systems was in almost complete agreement. There were no significant differences between the sample entropy of knee angle and joint angles of the sagittal plane by the comparisons of joint angle results extracted from different systems (p > 0.05). ICC (A, 1) indicated the validity was substantial. This is supported by the Bland-Altman plot of the joint angles at maximum flexion. Optical motion capture and single-camera sensors were collected simultaneously, making it feasible to capture stride-to-stride variability. In addition, the sample entropy of angles was close to the ground_truth in the sagittal plane, indicating that our video analysis could be used as a quantitative assessment of gait, making outdoor applications feasible.

A Portable Wearable Inertial System for Rehabilitation Monitoring and Evaluation of Patients With Total Knee Replacement.

Knee osteoarthritis is a degenerative disease, which greatly affects the daily life of patients. Total knee replacement (TKR) is the most common method to treat knee joint disorders and relieve knee pain. Postoperative rehabilitation exercise is the key to restore knee joint function. However, there is a lack of a portable equipment for monitoring knee joint activity and a systematic assessment scheme. We have developed a portable rehabilitation monitoring and evaluation system based on the wearable inertial unit to estimate the knee range of motion (ROM). Ten TKR patients and ten healthy adults are recruited for the experiment, then the system performance is verified by professional rehabilitation equipment Baltimore Therapeutic Equipment (BTE) Primus RS. The average absolute difference between the knee ROM and BTE Primus RS of healthy subjects and patients ranges from 0.16° to 4.94°. In addition, the knee ROM of flexion-extension and gait activity between healthy subjects and patients showed significant differences. The proposed system is reliable and effective in monitoring and evaluating the rehabilitation progress of patients. The system proposed in this work is expected to be used for long-term effective supervision of patients in clinical and dwelling environments.

Association of waist circumference with haemoglobin A1c and its optimal cutoff for identifying prediabetes and diabetes risk in the Chinese population.

Haemoglobin A1c (HbA1c) is a marker of glycaemic control in type 2 diabetes mellitus (T2DM). Increased waist circumference (WC) is known to be associated with T2DM. Therefore, we investigated the relationship of WC with HbA1c and explored its optimal cutoff for identifying prediabetes and diabetes risk. This study included 2339 participants between 18 and 84 years of age [mean (SD) age, 43.5 (11.9) years] with valid data on WC, HbA1c and related variables in the Shenzhen-Hong Kong United Network on Cardiovascular Disease study. Participants on anti-diabetic medications were excluded. Multiple linear regression was used to investigate the relationship between HbA1c and WC. Cutoff values of WC indicating an HbA1c level of 5.7% and 6.5% were also assessed using optimal binning. There was a significant linear relationship between WC and HbA1c in the overall population (B = 0.261, P < 0.001), men (B = 0.206, P < 0.001) and women (B = 0.311, P < 0.001). After adjustment for smoking, alcohol consumption, physical activity, hypertension, hypercholesterolaemia and age, the association remained significant in the overall population (B = 0.201, P < 0.001), men (B = 0.186, P < 0.001) and women (B = 0.182, P < 0.001). The optimal cutoff values of WC indicating an HbA1c level of 5.7% and 6.5% was 83 cm (entropy = 0.943) and 85 cm (entropy = 0.365) in men, and 78 cm (entropy = 0.922) and 86 cm (entropy = 0.256) in women. The linear relationship between WC and HbA1c in this study suggests that addressing central obesity issue is beneficial to people with T2DM or at risk of T2DM. WC cutoff values of 85 cm for men and 86 cm for women are appropriate for recommendation to undergo diabetes screening.

Design of an Unpowered Ankle-Foot Exoskeleton Used for Walking Assistance.

Enhance human walking and running is much more difficult compared to build a machine to help someone with disability. Unpowered ankle-foot exoskeletons are the current development trend due to their lightweight, wearable, and energy-free features, but the huge recognition and energy control system still affects their practicability. To refine the recognition and control system, we designed an unpowered soft ankle-foot exoskeleton with a purely mechanical self-adaptiveness clutch, which can realize the collection and release of energy according to different gait stage. Through switching and closing of this clutch, energy is collected when the ankle is doing negative work and released when the ankle is doing positive work. Results shows the unpowered ankle-foot exoskeleton at the stiffness of 12000 N/m could relieve muscles' load, with reduction of force by 52.3 % and 5.2%, and of power by 44.2% and 7.0%, respectively for soleus and gastrocnemius in simulation.Clinical Relevance-The proposed Unpowered Ankle-Foot Exoskeleton can both reduce muscle forces and powers. Hence, it can be used to assist walking of the elderly, others with neurocognitive disorders or leg diseases.

Automatic Fall Protection for Hips Based on Micromechanical Double Gas Cylinder Rapid Puncture and Bionic Capsule Inflation.

Wearable hip-protection airbags can effectively protect hip joints when elderly people fall. This has been studied all over the world, but similar products need to use special gas cylinders and replacement of new gas cylinders needs to return to the factory; The team previously designed a mechanical puncture protection system based on standard gas cylinders and standard threaded interfaces, but the airbag still has shortcomings such as the small protective area caused by a single gas cylinder. To solve the above problems, a set of wearable hip automatic protection systems based on micromechanical double gas cylinder rapid puncture (MDGCRP) is now designed. Through a large number of experiments, it was found that the response time of MDGCRP was 92ms and the execution time was 177.5ms. Compared with the single gas cylinder approach, the airbag provides greater protection to the hip while the filling time and module weight remain essentially unchanged. The system is triggered by physical and mechanical methods. Compared with chemical blasting or hot-melt methods, the system has the characteristics of low cost and consumables that can be safely and easily replaced by themselves.

Correction to: An explorative investigation of functional differences in plantar center of pressure of four foot types using sample entropy method.

In the original publication of the article the affiliation of Kamen Ivanov was inaccurate. The correct affiliation of Kamen Ivanov is given below.

3D Bioprinting of shear-thinning hybrid bioinks with excellent bioactivity derived from gellan/alginate and thixotropic magnesium phosphate-based gels.

3D Bioprinting is expected to become a strong tool for regenerative medicine, but satisfactory bioinks for the printing of constructs containing living cells are lacking due to the rigorous requirement of high printability and biocompatibility, which are often contradictory. Here, we have reported the development of a novel hybrid bioink by combining rigid gellan gum (GG), flexible sodium alginate (SA), and a bioactive substance thixotropic magnesium phosphate-based gel (TMP-BG). The ratio of these components was first optimized to obtain satisfactory gelating, mechanical, rheological, and printing properties. The formulated hybrid GG-SA/TMP-BG bioink had a good printability due to the shear-thinning and its multiple cross-linking by Mg2+ and Ca2+. The tunable mechanical performance of the hybrid bioink could simulate various extracellular matrices of the different tissues and support integrity of 3D printing constructs. Moreover, the hybrid bioink induced apatite deposition during immersion in simulated body fluids, and also promoted cell proliferation in vitro. MG-63 osteosarcoma cells were dispersed in the bioink and printed into 3D constructs. The cells exhibited good cell survival due to the shear-thinning property of the bioink and the ion concentration used for cross-linking. The proliferation rate of the cells also significantly exceeded those in non-printed samples. Confocal microscopy revealed a homogeneous distribution of cells in the printed constructs, and survival for more than 7 d. In vivo animal experiments showed that the hybrid bioink without cells could induce osteochondral repair. Therefore, this hybrid bioink has good printability, biocompatibility, mechanical support, and bioactivity, which is expected to have promising applications in 3D bioprinting.