Balance recovery after trips is affected by the type of tripping obstacles.

Occupational falls are often initiated by trips. Mechanical perturbations applied onto the tripped foot are different for different types of tripping obstacles. The present study aimed to determine how different types of tripping obstacles affect balance recovery after trips. Sixty-four healthy adults participated in an experimental study. They were instructed to perform several walking trials, during which two trips were randomly induced, one by a pole-like obstacle and the other by a board-like obstacle. Balance recovery after trips was measured and compared between the two obstacles. Results showed that the board-like obstacle led to longer step-off time, shorter recovery step duration, and smaller minimum hip height, suggesting that the risk of trip-initiated falls could be higher with the board-like obstacle vs. the pole-like obstacle. This finding presents the need for future research to consider the influence of obstacle type when exploring mechanisms for trips and falls.

Occupational falls are often initiated by trips. For better knowledge about trips and falls, this study examined the effects of tripping obstacles on balance recovery after trips. Knowledge obtained here could be useful for improving workers' awareness and assessment of the risk of trip-initiated falls in their workplace.

Enhancing squat movement classification performance with a gated long-short term memory with transformer network model.

Bodyweight squat is one of the basic sports training exercises. Automatic classification of aberrant squat movements can guide safe and effective bodyweight squat exercise in sports training. This study presents a novel gated long-short term memory with transformer network (GLTN) model for the classification of bodyweight squat movements. Twenty-two healthy young male participants were involved in an experimental study, where they were instructed to perform bodyweight squat in nine different movement patterns, including one acceptable movement defined according to the National Strength and Conditioning Association and eight aberrant movements. Data were acquired from four customised inertial measurement units placed at the thorax, waist, right thigh, and right shank, with a sampling frequency of 200 Hz. The results show that compared to state-of-art deep learning models, our model enhances squat movement classification performance with 96.34% accuracy, 96.31% precision, 96.45% recall, and 96.32% F-score. The proposed model provides a feasible wearable solution to monitoring aberrant squat movements that can facilitate performance and injury risk assessment during sports training. However, this model should not serve as a one-size-fits-all solution, and coaches and practitioners should consider individual's specific needs and training goals when using it.

A Low-Cost Instrumented Shoe System for Gait Phase Detection Based on Foot Plantar Pressure Data.

This paper presents a novel low-cost and fully-portable instrumented shoe system for gait phase detection. The instrumented shoe consists of 174 independent sensing units constructed based on an off-the-shelf force-sensitive film known as the Velostat conductive copolymer. A zero potential method was implemented to address the crosstalk effect among the matrix-formed sensing arrays. A customized algorithm for gait event and phase detection was developed to estimate stance sub-phases including initial contact, flat foot, and push off. Experiments were carried out to evaluate the performance of the proposed instrumented shoe system in gait phase detection for both straight-line walking and turning walking. The results showed that the mean absolute time differences between the estimated phases by the proposed instrumented shoe system and the reference measurement ranged from 45 to 58 ms during straight-line walking and from 51 to 77 ms during turning walking, which were comparable to the state of art.Clinical and Translational Impact Statement-By allowing convenient gait monitoring in home healthcare settings, the proposed system enables extensive ADL data collection and facilitates developing effective treatment and rehabilitation strategies for patients with movement disorders.

Development of a low-cost and user-friendly system to create personalized human digital twin.

Creating a digital twin has enormous potential in biomedical engineering. However, it is also technically challenging. No existing system can allow people who don't have the art-and-design background to create their own digital twin. To fill this gap, this study proposes a low-cost wearable system and a user-friendly framework for creating personalized digital twins with a fast speed and high fidelity. The personalized human digital twin can capture synchronized facial expressions, gaze direction, and whole-body movements for real-time rendering. The system simplifies the complex process of creating digital humans, and allows for the creation of data-driven characters without specialized skills.Clinical Relevance- This system can be used to help doctors keep track record of the patient's health status in a more visual and realistic way, supporting them in making more accurate clinical decisions, and facilitating a more detailed medical intervention.

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OBJECTIVES: To investigate the efficacy and required indicators of Children Neuropsychological and Behavioral Scale-Revision 2016 (CNBS-R2016) in the differential diagnosis of autism spectrum disorder (ASD) and global developmental delay (GDD). METHODS: A total of 277 children with ASD and 415 children with GDD, aged 18-48 months, were enrolled as subjects. CNBS-R2016 was used to assess the developmental levels of six domains, i.e., gross motor, fine motor, adaptive ability, language, social behavior, and warning behavior, and a total of 13 indicators on intelligence age and developmental quotient (DQ) were obtained as the input features. Five commonly used machine learning classifiers were used for training to calculate the classification accuracy, sensitivity, and specificity of each classifier. RESULTS: DQ of warning behavior was selected as the first feature in all five classifiers, and the use of this indicator alone had a classification accuracy of 78.90%. When the DQ of warning behavior was used in combination with the intelligence age of warning behavior, gross motor, and language, it had the highest classification accuracy of 86.71%. CONCLUSIONS: Machine learning combined with CNBS-R2016 can effectively distinguish children with ASD from those with GDD. The DQ of warning behavior plays an important role in machine learning, and its combination with other features can improve classification accuracy, providing a basis for the efficient and accurate differential diagnosis of ASD and GDD in clinical practice.

The Predictors of Unsafe Behaviors among Nuclear Power Plant Workers: An Investigation Integrating Personality, Cognitive and Attitudinal Factors.

Unsafe behaviors, such as violations and human errors, have long been recognized as the main causes of accidents in nuclear power plants (NPPs). However, personal factors that influence unsafe behaviors among NPP workers have not been well examined, especially in an integrated model. This study proposes an integrated contextual mediated model to examine personality, cognitive and attitudinal predictors of unsafe behaviors among commissioning workers at NPPs. The model was verified using structural equation modeling technique with survey data from 177 commissioning workers in two Chinese NPPs. Results show that personality traits (i.e., conscientiousness, neuroticism, openness and agreeableness), executive function and safety attitudes exerted significant effects on unsafe behaviors. In addition, the effects of agreeableness and executive function were partly mediated by safety attitudes. Both conscientiousness and neuroticism indirectly influenced unsafe behaviors through the mediating role of executive function. The findings shed light on the design of evidence-based interventions for safety performance in NPPs.

Input modality matters: A comparison of touch, speech, and gesture based in-vehicle interaction.

Innovative input devices are being available for in-vehicle information systems (IVISs). While they have the potential to provide enjoyable driving by enabling drivers to perform non-driving related tasks (NDRTs) in more natural ways, the associated distracting effects should be paid with more attention. The purpose of this exploratory study was to compare the effects of three novel input modalities, i.e., touchscreen-based interaction (TBI), speech-based interaction (SBI), and gesture-based interaction (GBI), on driving performance and driver visual behaviors. Moreover, we examined if the influence of different modalities would be moderated by the difficulty level of NDRTs. A total of 36 participants were invited to a simulated driving experiment where they were randomly assigned to one of the four groups (TBI, GBI, SBI or baseline) and completed three driving trials. The results showed that TBI led to the worse driving performance, as indicated by the significantly prolonged reaction time, reduced minimum time-to-collision, and increased variations in both longitudinal and lateral vehicle control. The deteriorated driving performance could be attributed, at least partially, to the intense visual demand induced by looking towards the touchscreen, as indicated by more and longer off-the-road glances. The adverse impacts of GBI were relatively smaller, but it still posed great crash risk by leading to a shorter minimum time-to-collision and less stable vehicle control compared to the baseline. SBI, although not completely equivalent to the baseline group, showed the minimum influence on driving and visual performance. Only very few interaction effects were found, suggesting that the effects of modality were quite robust across different NDRTs. It was concluded that SBI and GBI provided safer alternatives to in-vehicle interaction than TBI.

Characteristics of foot plantar pressure during turning in young male adults.

BACKGROUND: Turning gait is considered as a challenging motor task. However, only few existing studies reported turning biomechanics from the aspect of foot plantar pressure. RESEARCH QUESTION: This study aimed to investigate turning biomechanics by studying foot plantar pressure characteristics METHODS: Twelve young male participants were involved in this experimental study. They were instructed to perform turning tasks with different turning angles (i.e., 30°, 60°, and 90°). Foot plantar pressure was quantified by the force time integral (FTI) underneath seven plantar sub-areas. Analysis was carried out for different turning strategies (spin turns versus step turns), separately. RESULTS: The results showed that for small-angle spin turns, plantar pressure patterns changed at the early stage of the approaching step, suggesting a preparatory action for the increased lower limb range of motion in the transverse plane during turning; for step turns, an imbalance weight bearing mechanism was adopted when making large-angle turns to compensate for the centripetal force during turning. SIGNIFICANCE: The findings provide improved knowledge about turning biomechanics. They have practical implications for motion planning of lower-limb assistive devices for those with difficulties in turning.

Evaluation of force-time curve analysis methods in the isometric mid-thigh pull test.

The purpose of this study was to evaluate the manual and automatic analysis methods for force-time curve analysis of the isometric mid-thigh pull (IMTP) test. The visual analysis, first derivative analysis and threshold analysis methods were used to analyse onset time and time-specific forces at 50 ms, 90 ms, 200 ms and 250 ms on the force-time curve. Ninety-three collegiate sports athletes' trials were selected and analysed by each method. The visual analysis method was set as the reference method for paired comparisons with the first derivative analysis method and threshold analysis method. Onset time comparisons revealed that the first derivative analysis method was comparable with the visual analysis method with average difference at about 30 ms. Results from the weighted least products regression analysis and the Bland-Altman analysis showed that large fixed bias confounded by proportional bias existed in the threshold analysis method, and time-specific force variables obtained from the first derivative analysis method were closer to those from the visual analysis method when compared with the threshold analysis method. These findings suggest that the first derivative analysis method could be an effective tool for force-time curve analysis of the IMTP test.

Use of Oculomotor Behavior to Classify Children with Autism and Typical Development: A Novel Implementation of the Machine Learning Approach.

This study segmented the time series of gaze behavior from nineteen children with autism spectrum disorder (ASD) and 20 children with typical development in a face-to-face conversation. A machine learning approach showed that behavior segments produced by these two groups of participants could be classified with the highest accuracy of 74.15%. These results were further used to classify children using a threshold classifier. A maximum classification accuracy of 87.18% was achieved, under the condition that a participant was considered as 'ASD' if over 46% of the child's 7-s behavior segments were classified as ASD-like behaviors. The idea of combining the behavior segmentation technique and the threshold classifier could maximally preserve participants' data, and promote the automatic screening of ASD.

Influence of load knowledge on lifting biomechanics.

Objectives. Findings from previous studies implied that appropriately controlling load knowledge might help improve the biomechanical performance during lifting tasks. However, only load weight knowledge was often discussed in previous studies. The current study aimed to complement the existing studies and provide improved knowledge about the influence of load knowledge on lifting biomechanics. Methods. Twenty-four healthy male participants were recruited and instructed to perform symmetric lifting tasks with different load weights under different load knowledge conditions. Load weights were set at three levels (40, 80 and 120%) of each participant's maximum acceptable lifting capacity. The examined load knowledge conditions included 'no knowledge' condition, 'weight known' condition, 'fragile material known' condition and 'weight and fragile material known' condition. Results. We found that when knowing fragility information about lifting materials, workers tended to be more cautious by adopting a less dynamic motion pattern during the landing phase, as evidenced by decreases of 6-8% in elbow joint acceleration. The 'cautious' lifting pattern when fragility load knowledge was presented could contribute to reduced risk of lower back disorder. Conclusion. This finding could help to develop lower back disorder prevention interventions to improve occupational safety and health.

Characteristics of Visual Fixation in Chinese Children with Autism During Face-to-Face Conversations.

Few eye tracking studies have examined how people with autism spectrum disorder (ASD) visually attend during live interpersonal interaction, and none with the Chinese population. This study used an eye tracker to record the gaze behavior in 20 Chinese children with ASD and 23 children with typical development (TD) when they were engaged in a structured conversation. Results demonstrated that children with ASD looked significantly less at the interlocutor's mouth and whole-face, and more at background. Additionally, gaze behavior was found to vary with the conversational topic. Given the great variability in eye tracking findings in existing literature, future explorations might consider investigating how fundamental factors (i.e., participant's characteristics, tasks, and context) influence the gaze behavior in people with ASD.

Identification of balance recovery patterns after slips using hierarchical cluster analysis.

Accidental falls often result from loss of balance initiated by slips. People may adopt different balance recovery patterns after slips which could affect recovery outcomes. The present study aimed to identify balance recovery patterns after slips and to determine whether these balance recovery patterns could be associated with different levels of slip-induced fall likelihood. Sixty young (age 24.2 ± 2.1 years) participants were involved in an experimental study. They were instructed to walk on a linear walkway, where unexpected slips were induced when stepping onto a removable vinyl tile sheet covered with water-detergent mixture. One hundred and fifty slip trials were obtained, including 85 successful balance recovery trials and 65 failed balance recovery trials (i.e., fall trials). Hierarchical cluster analysis was used to classify balance recovery patterns based on the kinematic measures of both feet over the period from 100 to 300 ms after heel contact of the slipping foot. Three balance recovery patterns were identified, and these balance recovery patterns were found to be associated with different levels of slip-induced fall likelihood. Findings from the present study can contribute to better understanding of balance recovery mechanisms associated with slips, and guide developing and evaluating fall prevention interventions.

Typing with mobile devices: A comparison of upper limb and shoulder muscle activities, typing performance and perceived workload under varied body postures, typing styles and device types.

This study aimed to examine the effects of body posture, typing style and device type on upper limb and shoulder muscle activities, typing performance and perceived workload while typing with mobile devices. Participants were asked to type with two mobile devices (i.e., a tablet and a smartphone) under three postures and in two typing styles. Muscle activity was recorded for four upper limb and shoulder muscles on both sides with surface electromyography. Results showed that body posture and typing style yielded significant effects on tying performance, perceived workload, and muscle activities in the forearm, upper arm and shoulder. Typing with a tablet was more accurate and had greater muscle activities in the upper arm and forearm on both sides than typing with a smartphone. The findings may be useful in developing evidence-based guidelines for the wise use of mobile devices and for the prevention of risks for musculoskeletal disorders.

Influence of Load Knowledge on Biomechanics of Asymmetric Lifting.

BACKGROUND: Load knowledge has been identified as a factor affecting the risk of low back pain (LBP) during symmetric lifting. However, the effects of load knowledge in asymmetric lifting tasks have not been reported yet. The purpose of this study was to investigate the load knowledge influence on lifting biomechanics in asymmetric lifting tasks; Methods: Twenty-four male adults were recruited to complete a psychophysical lifting capacity test and a simulated asymmetric lifting task. The lifting task was set with load knowledge of 'no knowledge' (NK), 'weight known' (WK), 'fragile material known' (FK), and 'weight and fragile material known' (WFK) for different lifting load weights. Trunk kinematics and kinetics were collected and analyzed; Results: When fragility information was presented, trunk sagittal flexion acceleration, lateral flexion velocity and acceleration, and average lateral bending moment were significantly lowered at the deposit phase. Lifting a high load weight was found to significantly increase low back sagittal bending moment at the lifting phase and low back moments of all three dimensions at the deposit phase; Conclusions: The decrease of trunk kinematic load suggests that providing material fragility information to workers in asymmetric lifting tasks would be effective in reducing their risk of LBP.

Excessive and less complex body movement in children with autism during face-to-face conversation: An objective approach to behavioral quantification.

The majority of existing studies investigating characteristics of overt social behavior in individuals with autism spectrum disorder (ASD) relied on informants' evaluation through questionnaires and behavioral coding techniques. As a novelty, this study aimed to quantify the complex movements produced during social interactions in order to test differences in ASD movement dynamics and their convergence, or lack thereof, during social interactions. Twenty children with ASD and twenty-three children with typical development (TD) were videotaped while engaged in a face-to-face conversation with an interviewer. An image differencing technique was utilized to extract the movement time series. Spectral analyses were conducted to quantify the average power of movement, and the fractal scaling of movement. The degree of complexity matching was calculated to capture the level of behavioral coordination between the interviewer and children. Results demonstrated that the average power was significantly higher (p < 0.01), and the fractal scaling was steeper (p < 0.05) in children with ASD, suggesting excessive and less complex movement as compared to the TD peers. Complexity matching occurred between children and interviewers, but there was no reliable difference in the strength of matching between the ASD and TD children. Descriptive trends in the interviewer's behavior suggest that her movements adapted to match both ASD and TD movements equally well. The findings of our study might shed light on seeking novel behavioral markers of ASD, and on developing automatic ASD screening techniques during daily social interactions. LAY SUMMARY: By implementing an objective behavioral quantifying technique, our study demonstrated that children with autism had more body movement during face-to-face conversation, and they moved in a less complex way. The current diagnosis of autism heavily relies on doctor's experiences. These findings suggest a potential that autism might be automatically screened during daily social interactions.

The roles of lower-limb joint proprioception in postural control during gait.

The objective of the present study was to investigate the roles of lower-limb joint proprioception in postural control during gait. Seventy-two healthy adults including 36 younger and 36 older adults participated in two experimental sessions, i.e., lower-limb joint proprioception assessment session and gait assessment session. Lower-limb joint proprioception was assessed by joint position sense errors measured at the ankle, knee and hip of the dominant side. Postural control during gait was characterized by step length, step width and local dynamic stability. Results showed that hip proprioception contributed the most to postural control during gait among the lower-limb joint proprioception components, and that mechanisms for the hip proprioception effects were different between age groups. These findings highlighted the importance of incorporating hip proprioception enhancement exercises in postural control training programs, and the necessity of considering age-related differences in the effects of hip proprioception when designing these exercises.

Identifying Autism with Head Movement Features by Implementing Machine Learning Algorithms.

Our study investigated the feasibility of using head movement features to identify individuals with autism spectrum disorder (ASD). Children with ASD and typical development (TD) were required to answer ten yes-no questions, and they were encouraged to nod/shake head while doing so. The head rotation range (RR) and the amount of rotation per minute (ARPM) in the pitch (head nodding direction), yaw (head shaking direction) and roll (lateral head inclination) directions were computed, and further fed into machine learning classifiers as the input features. The maximum classification accuracy of 92.11% was achieved with the decision tree classifier with two features (i.e., RR_Pitch and ARPM_Yaw). Our study suggests that head movement dynamics contain objective biomarkers that could identify ASD.

Random and Short-Term Excessive Eye Movement in Children with Autism During Face-to-Face Conversation.

This study investigated the oculomotor performance in children with autism spectrum disorder (ASD) during a face-to-face conversation. A head mounted eye tracker recorded the eye movements in 20 children with ASD and 23 children with typical development (TD). Group comparisons were conducted on the randomness and the quantity of eye movement. The amount of time needed to reveal group difference was also examined. Results showed that the randomness of eye movement was significantly higher at all examined time durations, and the amount of eye movement was significantly greater within 3 s in the ASD group. These findings demonstrated an atypical pattern of oculomotor dynamics in children ASD, which might facilitate the objective identification of ASD during daily social interaction.