Movements Of Body Parts Research Articles

The Effect of Guided Motor Imagery on Functional Gait Performance in Post Stroke Patients

Purpose: Restoration of independent walking is the major goal of rehabilitation after stroke. Walkingdifficulty hinders community level participation of an individual, affecting quality of life. Earliest activationof locomotion concerned cortical areas is important to achieve near normal locomotion after rehabilitation.Motor imagery (MI) is a process of imagination of body part movement without actually moving it and it isfound that MI activates same cortical areas which are activated during actual movement. MI enhances motorplanning, causes neural adaptations to improve voluntary skeletal muscle strength and increases firing atlocal interneurons as well. There is limited evidence available regarding the effect of guided motor imagery(guided MI) on functional gait performance in post stroke patients. Hence, purpose of this study is to see theeffect of guided MI on functional gait performance in post stroke patients. Aim: To study effect of guidedMI on functional gait performance in post stroke patients. Objective: To assess and compare functionalgait performance in post stroke patients with and without guided MI. Method: Prospective, ExperimentalRandomized Control Trial. Result: Study results showed that functional gait performance has improved inpost stroke patients due to guided MI reflected by significant p values during analysis. Conclusion: Theabove study concludes that application of guided MI improves functional gait performance in post strokepatients as compared to conventional treatment alone, enhancing their functional independence and qualityof life.

Autocorrelation-based method to identify disordered rhythm in Parkinson's disease tasks: A novel approach applicable to multimodal devices.

ObjectiveWe aim to propose a novel method of evaluating the degree of rhythmic irregularity during repetitive tasks in Parkinson’s disease (PD) by using autocorrelation to extract serial perturbation in the periodicity of body part movements as recorded by objective devices.MethodsWe used publicly distributed sequential joint movement data recorded during a leg agility task or pronation-supination task. The sequences of body part trajectory were processed to extract their short-time autocorrelation (STACF) matrices; the sequences of single task conducted by participants were then divided into two clusters according to their similarity in terms of their STACF representation. The Unified Parkinson’s Disease Rating Scale sub-score rated for each task was compared with cluster membership to obtain the area under the curve (AUC) to evaluate the discrimination performance of the clustering. We compared the AUC with those obtained from the clustering of the raw sequence or short-time Fourier transform (STFT).ResultsIn classifying the pose estimator-based trajectory data of the knee during the leg agility task, the AUC was the highest when the STACF sequence was used for clustering instead of other types of sequences with up to 0.815, being comparable to the results reported in the original analysis of the data using an approach different from ours. In addition, in classifying another dataset of accelerometer-based trajectory data of the wrist during a pronation-supination task, the AUC was again highest up to 0.785 when clustering was performed using the STACF rather than other types of sequence.ConclusionOur autocorrelation-based method achieved a fair performance in detecting sequences with irregular rhythm, suggesting that it might be used as another evaluation strategy that is potentially widely applicable to qualify the disordered rhythm of PD regardless of the kinds of task or the modality of devices, although further refinement is needed.

Simultaneous feedback control for joint field and motion correction in brain MRI

T2*-weighted gradient-echo sequences count among the most widely used techniques in neuroimaging and offer rich magnitude and phase contrast. The susceptibility effects underlying this contrast scale with B0, making T2*-weighted imaging particularly interesting at high field. High field also benefits baseline sensitivity and thus facilitates high-resolution studies. However, enhanced susceptibility effects and high target resolution come with inherent challenges. Relying on long echo times, T2*-weighted imaging not only benefits from enhanced local susceptibility effects but also suffers from increased field fluctuations due to moving body parts and breathing. High resolution, in turn, renders neuroimaging particularly vulnerable to motion of the head. This work reports the implementation and characterization of a system that aims to jointly address these issues. It is based on the simultaneous operation of two control loops, one for field stabilization and one for motion correction. The key challenge with this approach is that the two loops both operate on the magnetic field in the imaging volume and are thus prone to mutual interference and potential instability. This issue is addressed at the levels of sensing, timing, and control parameters. Performance assessment shows the resulting system to be stable and exhibit adequate loop decoupling, precision, and bandwidth. Simultaneous field and motion control is then demonstrated in examples of T2*-weighted in vivo imaging at 7T.

Nanofiber-based wearable energy harvesters in different body motions

In this study, flexible energy harvesters based on lead zirconate titanate (PZT)/shape memory polyurethane (SMPU) nanofibers were prepared and made wearable for energy harvesting from human body movements while ensuring flexibility. The results obtained showed that there is a relationship between the piezoelectric and energy harvesting properties of the proposed PZT/SMPU energy harvesters, and the alignment degrees and motion modes. The 0°-aligned energy harvester—wherein nanofibers are parallel to the longitudinal direction—showed higher piezoelectric properties and induced higher output voltages because of the bending motion compared to nanofibers aligned randomly-, at 90°-, and at 45°-. Practical tests showed that flexible energy harvesters can efficiently convert mechanical energy into electricity when subject to different body motions such as bending, twisting, and applied pressure. The maximum output voltages generated by energy harvesters with 0°- and 45°-aligned nanofibers were 537 and 55 mV when they were subjected to finger bending and wrist twisting motions, respectively; this represents an increase of at least 28% compared to that of other samples. Therefore, these findings provide insights and strategies related to the optimal arrangement of nanofibers in wearable energy harvesters and improvement in their energy harvesting efficiency with respect to different body part motions.

ANALISA POSTUR KERJA OPERATOR BAGIAN FINISHING MENGGUNAKAN METODE OVAKO WORK ANALYSIS SYSTEM (OWAS) DI CV. SARANA TEKNIK

The purpose of study is analysis the work posture of the finishing section on the CV. Sarana Teknik, in order to reduce musculoskeletal disorders using the Nordic Body Map, and the Ovako Work Analysis System (OWAS). CV. Sarana Teknik is an industry engaged in processing plastic pellets into various products on demand. These products are medicine caps and toys that are relatively small in size. The study was conducted in the finishing section with 6 operators. Based on the Nordic Body Map questionnaire, 49% of workers or 3 of 6 workers stated that they were somewhat sick to the point where they were examined at 28 points of the body. Then the work attitude analysis that defines the movement of body parts of the back, arms, legs and weight lifted using the Ovako Work Analysis System (OWAS). The results of this study are the body part is very painful, which is dominantly felt by all operators, is back by 100%. The observed work posture is the taking and tidying posture, the result of the analysis is the taking work posture is category 2 which is a dangerous attitude on the musculoskeletal system which results in a significant tension effect so that the posture needs improvement. As for the tidying work posture, category 1 is an attitude that has no problems so this attitude does not need to be improved.

Keyframe-based multi-contact motion synthesis

Most of the human daily activities include acyclic multi-contact motions. Yet, generating such motions is challenging because of its high-dimensional and nonlinear solution space made by combinations of individual movements of body parts. In this paper, we present a novel keyframe-based framework to automatically generate multi-contact character motions. Our system consists of two components: key-pose planning and interpolation. Given initial and goal poses in which each contact can be repositioned at most one time during the transition, our key-pose planning step generates intermediate key-poses that represent contact changes, taking into account a set of principles for goal-directed movements. Next, the key-poses of each joint are independently interpolated to generate an acyclic multi-contact motion. We demonstrate that our framework can synthesize plausible interaction motions with a number of man-made objects, such as chairs and bicycles, without using any motion data. In addition, we show the scalability of our method by creating a long-term motion of climbing a ladder.

RETRACTED ARTICLE: Human adaptive mechatronics system integrated with cybernetics loop using neuromuscular controller in occupational therapy for elderly person with disability

Human adaptive mechatronics (HAM) device is operated using neuromuscular interface controller. The muscle activity is monitored with the help of electromyogram (EMG) signals. The change in signal strength due to the volunteering movement of body parts is detected by placing few electrodes on the skin surface. EMG signal is used as the control signal and it gives the movement coordination. The amplitude of the signal changes with respect to the muscle activity. The HAM device is made to operate depending upon the amplitude changes in the generated EMG signal. The option of using cybernetic loop facilitates the balance of the control error and the delayed response time of the system. This paper elaborates the working of human adaptive neuromuscular interface controller in mechatronics device and the simulation is carried out in real time approach for the different muscle activity mainly between the two actions: volunteer motion and intended motion.

Modern approaches to improving the system for assessing the complexity of exercises in acrobatic rock and roll

The article presents a methodology for systematizing the exercise by the degree of difficulty. It was found that, based on the principles of biomechanics, when performing any movement, an athlete needs to create a dynamic effort, which determines the kinematics of movements of body parts. Assessing the complexity of the movements performed by the athlete, one must take into account the degree of dynamic efforts, which are determined by the energy expenditure to acquire the required posture. It is also necessary to take into account the static muscle tension to maintain it, in the process of performing a given exercise. And finally, the degree of dynamic effort of the muscle group to return to the final pose. As a result of the research, regularities have been obtained that allow us to provide a substantiated structure for constructing a test assessment of tasks for the selection of exercises when organizing the training process and moving to a new level of the difficulty rank of the qualifying task.

Optimizing Modifiable and Lifestyle-related Factors in the Prevention of Dementia Disorders with Special Reference to Alzheimer, Parkinson and Autism Diseases

Dementia is a syndrome and an umbrella term that encompasses Alzheimer, Parkinson and autism diseases. These diseases are by far the most common cause of dementia; therefore this investigation will chiefly include these disorders, with a limited discussion of few other disorders related to dementia. Alzheimer’s disease (AD) is characterized by the accumulation of cerebral β-amyloid plaques, tau proteins and memory loss; Parkinson by the deterioration of brain cells which regulate the movement of body parts and produce dopamine; and autism by abnormalities of social disorder and difficulty in communicating and forming relationships. Alzheimer’s disease and cognitive impairment in dementia are age-related and manageable only with early diagnosis and prevention. Data based on several decades of research has shown that the major factors responsible for the induction of inflammation in dementia and many chronic diseases are infections, obesity, alcohol, radiation, environmental pollutants, improper nutrition, lack of physical activity, depression, anxiety, genetic factors, and sleep deprivation. There are some studied preventive measures for dementia including continued physical activity and consuming predominantly a plant-based Mediterranean diet comprising olive oil and foods containing flavonoids and other phytochemicals having strong antioxidant and anti-inflammatory properties and along with management of chronic conditions.

Observing Actions Through Immersive Virtual Reality Enhances Motor Imagery Training.

Visual information plays an essential role in enhancing neural activity during mental practices. Previous research has shown that using different visual scenarios during mental practices that involve imagining the movement of a specific body part may result in differences in performance. Many of these scenarios utilize the concept of embodiment, or one's observation of another entity to be a part of oneself, to improve practice quality of the imagined body movement. We therefore hypothesized that applying immersive virtual reality headsets, with their ability to provide rich immersion and illusion by presenting egocentrically simulated virtual scenarios, and action observation to motor imagery practice will result in significant improvement. To explore the possible synergy between immersive systems and motor imagery, we analyzed the electroencephalogram signals of our participants as they were presented the same virtual hand movement scenario with two different mediums: an immersive virtual reality headset and a monitor display. Our experimental results provide evidence that the immersive virtual reality headsets induced improved rhythmic patterns with better discriminating spatial features from the brain compared to the monitor display. These findings suggest that the use of immersive virtual reality headsets, with the illusion and embodiment they provide, can effectively improve motor imagery training.

Developing Shooter Game Interaction using Eye Movement Glasses

A quadriplegic is a paralysis that affects limitations in some physical movements and psychological disorders. They have limited media to interact with computers so a suitable solution is needed in the form of a media that can recognize other body parts movements which in this research uses eye movement. one of the solutions to this problem is to propose alternative technologies to interact and play games. We propose a simple technique by using a camera mounted on the glasses that will take the eye area. This technique will help reduce unnecessary parts of eye detection so that performance increases. The eyes will be processed using basic image processing and then determined the center position of the pupil using the Mean method. This system consists of pupil movements for pointer motion control and blinking of eyes for shooting. The performance test of this method toward the system, which has used 10 people with 7 experiments, shows an accuracy of 84.86 percent, the speed of movement with a duration of 2.22 seconds and the speed of response blinking with a duration of 0.026 seconds. In addition, we can distinguish between intentional blink and unintentional blink in which intentional blink has a duration of 0.30 seconds and unintentional 0.12 seconds. It can be concluded that by using this method and this technique is able to achieve good accuracy and also able to use intentional blink as shoot trigger.

Marker-Based Movement Analysis of Human Body Parts in Therapeutic Procedure.

Movement analysis of human body parts is momentous in several applications including clinical diagnosis and rehabilitation programs. The objective of this research is to present a low-cost 3D visual tracking system to analyze the movement of various body parts during therapeutic procedures. Specifically, a marker based motion tracking system is proposed in this paper to capture the movement information in home-based rehabilitation. Different color markers are attached to the desired joints’ locations and they are detected and tracked in the video to encode their motion information. The availability of this motion information of different body parts during the therapy can be exploited to achieve more accurate results with better clinical insight, which in turn can help improve the therapeutic decision making. The proposed framework is an automated and inexpensive motion tracking system with execution speed close to real time. The performance of the proposed method is evaluated on a dataset of 10 patients using two challenging matrices that measure the average accuracy by estimating the joints’ locations and rotations. The experimental evaluation and its comparison with the existing state-of-the-art techniques reveals the efficiency of the proposed method.

Using TEMPO-oxidized-nanocellulose stabilized carbon nanotubes to make pigskin hydrogel conductive as flexible sensor and supercapacitor electrode: Inspired from a Chinese cuisine

Inspired from a famous Chinese pigskin jelly cuisine, flexible and conductive hydrogel was prepared by incorporating 2,2,6,6-tetramethylpiperidine-1-oxy radical (TEMPO)-oxidized-nanocellulose (TC) stabilized carbon nanotubes (CNT) into pigskin matrix (PS) in the present study. Due to the assistance of the TC, the CNT could homogeneously disperse within the PS and build strong and integrated conductive network. The prepared conductive hydrogel (TC-s-CNT-PS) was then used as the flexible conductive sensor for detecting daily human body motion. The supercapacitance properties of the conductive hydrogel was also studied. The results indicated that the TC-s-CNT-PS could quickly and accurately response to the cyclic tensile and pressing forces with stable and repeatable resistance change signals. Moreover, the TC-s-CNT-PS was able to detect real-time human body motion of different body parts. Besides, the prepared hydrogel also had a specific capacitance of ~65 F/g with 60% of the capacitance retention after 2000 consecutive charge-discharge cycles. The present study provides a new view to utilize animal food waste for the construction of high-performance conductive electrical devices as flexible sensors and supercapacitor electrode.

A robust method for VR-based hand gesture recognition using density-based CNN

Many VR-based medical purposes applications have been developed to help patients with mobility decrease caused by accidents, diseases, or other injuries to do physical treatment efficiently. VR-based applications were considered more effective helper for individual physical treatment because of their low-cost equipment and flexibility in time and space, less assistance of a physical therapist. A challenge in developing a VR-based physical treatment was understanding the body part movement accurately and quickly. We proposed a robust pipeline to understanding hand motion accurately. We retrieved our data from movement sensors such as HTC vive and leap motion. Given a sequence position of palm, we represent our data as binary 2D images of gesture shape. Our dataset consisted of 14 kinds of hand gestures recommended by a physiotherapist. Given 33 3D points that were mapped into binary images as input, we trained our proposed density-based CNN. Our CNN model concerned with our input characteristics, having many 'blank block pixels', 'single-pixel thickness' shape and generated as a binary image. Pyramid kernel size applied on the feature extraction part and classification layer using softmax as loss function, have given 97.7% accuracy.

Somatosensory attentional modulations during pain-related movement execution.

Pain serves to protect against bodily threat, and therefore initiates protective responses such as attending toward threat-relevant information. Since pain is often exacerbated by executing movements, these motor actions may serve as cues for pain. Up to date, however, pain-related attention during movement remains largely unexplored. While it has been shown that the preparation of a pain-related movement leads to enhanced processing of somatosensory information, it is unclear how the actual execution of a movement interacts with somatosensory attention. In the current study, we examined whether somatosensory processing is enhanced at a moving body part when the movement is expected to be associated with pain. Participants were asked to execute hand movements which were occasionally followed by a pain stimulus. To measure somatosensory attention, a task-irrelevant, innocuous tactile probe was presented on either hand to evoke a somatosensory evoked potential (SEP). The results showed an elevation of the N120 SEP at the hand performing a potentially painful movement, indicating heightened attention toward tactile information at the threatened moving hand compared to the non-threatened hand. Additionally, the P200 SEP also showed enlarged responses when performing a pain-related movement compared to a no-pain-related movement. These results show that not only the anticipation, but also the execution of pain-related movements, may modulate the processing of somatosensory input, driven by attentional processes.

The Deposition of Human Remains Inside Chalcolithic Ditched Enclosures: Ditch 5 at Marroquíes (Jaén, Spain)

In the last few decades, the discovery of large ditched enclosures in Iberia has revealed the diversity and complexity of deposition and manipulation of human bone remains. Alongside traditional ritual burials (mainly megalithic tombs and hypogea), fragmented and scattered human bones mixed with other kinds of material culture began to appear in many features. This is the case for Ditch 5 at Marroquíes, which offers an excellent opportunity to explore this ritual behaviour. Based on a multi-proxy approach, three main conclusions can be drawn: 1) the skeletal elements present show deliberate selection of particular categories of bones; 2) depositional episodes included the remains of people who died at different points in time and were subject to different taphonomic processes, and 3) mobility patterns indicate that all individuals, with one possible exception, were local. The movement and manipulations of body parts may reflect the active role of people after death as social and symbolic elements that retain agency and capacity for action.

Seeing your own or someone else's hand moving in accordance with your action: The neural interaction of agency and hand identity.

Forward models can predict sensory consequences of self‐action, which is reflected by less neural processing for actively than passively generated sensory inputs (BOLD suppression effect). However, it remains open whether forward models take the identity of a moving body part into account when predicting the sensory consequences of an action. In the current study, fMRI was used to investigate the neural correlates of active and passive hand movements during which participants saw either an on‐line display of their own hand or someone else's hand moving in accordance with their movement. Participants had to detect delays (0–417 ms) between their movement and the displays. Analyses revealed reduced activation in sensory areas and higher delay detection thresholds for active versus passive movements. Furthermore, there was increased activation in the hippocampus, the amygdala, and the middle temporal gyrus when someone else's hand was seen. Most importantly, in posterior parietal (angular gyrus and precuneus), frontal (middle, superior, and medial frontal gyrus), and temporal (middle temporal gyrus) regions, suppression for actively versus passively generated feedback was stronger when participants were viewing their own compared to someone else's hand. Our results suggest that forward models can take hand identity into account when predicting sensory action consequences.

Particle Swarm Optimization Algorithm to Optimize the Activity Patterns of Internal Globus Pallidus in Parkinson Disease

Parkinson disease, one of the widely known brain disorders, affects the movement of body parts due to dopamine reduction in the basal ganglia. In this paper, a model of internal globuspallidus is taken into consideration for a primate suffering from Parkinson disease. The discharge patterns generated for a primate suffering from Parkinson disease are compared with the discharge patterns of a healthy primate. The lags in the discharge patterns of primate with Parkinson disease due to slow movement are shown in the result section of the paper. On the basis of analysis of the model, four parameters have been optimized to remove these lags; which are membrane potential from GPe to GPi (denoted by ), membrane potential from STN to GPi (denoted by ), synaptic conductance from GPe to GPi (denoted by ) and synaptic conductance from STN to GPi (denoted by ) as the model is most sensitive to these four parameters among all the parameters taken into consideration. Optimization of these parameters has been carried out using particle swarm optimization algorithm over a time span of 300 msec. A qualitative comparison has been made using correlation coefficient computed between the discharge patterns for a healthy primate and primate with Parkinson disease. The value of correlation coefficient turns out to be 0.9994 showing very high degree of overlap between the two discharge patterns, and validates the high degree of accuracy of the results obtained by particle swarm optimization algorithm.

Neurosurgical lesions to sensorimotor cortex do not impair action verb processing

There is ongoing debate regarding the role that sensorimotor regions play in conceptual processing, with embodied theories supporting their direct involvement in processing verbs describing body part movements. Patient lesion studies examining a causal role for sensorimotor activation in conceptual task performance have suffered the caveat of lesions being largely diffuse and extensive beyond sensorimotor cortices. The current study addresses this limitation in reporting on 20 pre-operative neurosurgical patients with focal lesion to the pre- and post-central area corresponding to somatotopic representations. Patients were presented with a battery of neuropsychological tests and experimental tasks tapping into motor imagery and verbal conceptual verb processing in addition to neurophysiological measures including DTI, fMRI, and MEP being measured. Results indicated that left tumor patients who presented with a lesion at or near somatotopic hand representations performed significantly worse on the mental rotation hand task and that performance correlated with MEP amplitudes in the upper limb motor region. Furthermore, performance on tasks of verbal processing was within the normal range. Taken together, while our results evidence the involvement of the motor system in motor imagery processes, they do not support the embodied view that sensorimotor regions are necessary to tasks of action verb processing.

Antibacterial, Flexible, and Conductive Membrane Based on MWCNTs/Ag Coated Electro-Spun PLA Nanofibrous Scaffolds as Wearable Fabric for Body Motion Sensing.

In the present study, flexible and conductive nanofiber membranes were prepared by coating PLA nanofibrous scaffolds with carbon nanotubes and silver nanoparticles. The morphology and structure of the prepared membrane was characterized, as well as its mechanical properties, electrical sensing behavior during consecutive stretching-releasing cycles and human motion detecting performance. Furthermore, the antibacterial properties of the membrane was also investigated. Due to the synergistic and interconnected three-dimensional (3D) conductive networks, formed by carbon nanotubes and silver nanoparticles, the membrane exhibited repeatable and durable strain-dependent sensitivity. Further, the prepared membrane could accurately detect the motions of different body parts. Accompanied with promising antibacterial properties and washing fastness, the prepared flexible and conductive membrane provides great application potential as a wearable fabric for real-time body motion sensing.