Movements Of Different Body Parts Research Articles

Integrating mind and body: Investigating differential activation of nodes of the default mode network.

The default mode network (DMN) is a large-scale brain network tightly correlated with self and self-referential processing, activated by intrinsic tasks and deactivated by externally-directed tasks. In this study, we aim to investigate the novel approach of default mode activation during progressive muscle relaxation and examine whether differential activation patterns result from the movement of different body parts. We employed neuroimaging to investigate DMN activity during simple body movements, while performing progressive muscle relaxation. We focused on differentiating the neural response between facial movements and movements of other body parts. Our results show that the movement of different body parts led to deactivation in several DMN nodes, namely the temporal poles, hippocampus, medial prefrontal cortex (mPFC), and posterior cingulate cortex. However, facial movement induced an inverted and selective positive BOLD pattern in some of these areas precisely. Moreover, areas in the temporal poles selective for face movement showed functional connectivity not only with the hippocampus and mPFC but also with the nucleus accumbens. Our findings suggest that both conceptual and embodied self-related processes, including body movements during progressive muscle relaxation, may be mapped onto shared brain networks. This could enhance our understanding of how practices like PMR influence DMN activity and potentially offer insights to inform therapeutic strategies that rely on mindful body movements.

Transparent, High Stretchable, Environmental Tolerance, and Excellent Sensitivity Hydrogel for Flexible Sensors and Capacitive Pens.

The prospect of ionic conductive hydrogels in multifunctional sensors has generated widespread scientific interest. The new generation of flexible materials should be combined with superior mechanical properties, high conductivity, transparency, sensitivity, good self-restoring fatigue properties, and other multifunctional characteristics, while the current materials are difficult to meet these requirements. Herein, we prepared poly(acrylamide-acrylic acid) (P(AM-AA))/gelatin/glycerol-Al3+ (PG1G2A) ionic conducting hydrogel by one-pot polymerization under UV light. The prepared PG1G2A ionic conductive hydrogel had high tensile strength (539.18 kPa), excellent tensile property (1412.96%), good fast self-recovery and fatigue resistance, high transparency (>80%), excellent moisturizing, and antifreezing/drying properties. In addition, the ionic conductive hydrogel-based strain sensor can respond to mechanical stimulation and generate accurate, stable, and recyclable electrical signals, with excellent sensitivity (GF 5.81). In addition, the PG1G2A hydrogel could be used as flexible wearable devices for monitoring multiple strain and subtle movements of different body parts at different temperatures. Interestingly, the PG1G2A hydrogel capacitive pen embedded in the mold can be used to write and draw on the screen of a phone or tablet. This new multifunctional ionic conducting hydrogel shows broad application prospects in E-skin, motion monitoring, and human-computer interaction in extreme environments.

A motor association area in the depths of the central sulcus

Cells in the precentral gyrus directly send signals to the periphery to generate movement and are principally organized as a topological map of the body. We find that movement-induced electrophysiological responses from depth electrodes extend this map three-dimensionally throughout the gyrus. Unexpectedly, this organization is interrupted by a previously undescribed motor association area in the depths of the midlateral aspect of the central sulcus. This ‘Rolandic motor association’ (RMA) area is active during movements of different body parts from both sides of the body and may be important for coordinating complex behaviors.

On That <em>Toy-Being</em> of Generative Art Toys

On That <em>Toy-Being</em> of Generative Art Toys

Research on Multiperson Motion Capture System Combining Target Positioning and Inertial Attitude Sensing Technology

The purpose of this study is to solve the problems of multiple targets, poor accuracy, and inability to obtain displacement information in motion capture. Based on fusion target positioning and inertial attitude sensing technology, Unity3D is employed to create 3D scenes and 3D human body models to read real-time raw data from inertial sensors. Furthermore, a gesture fusion algorithm is used to process the raw data in real time to generate a quaternion, and a human motion capture system is designed based on inertial sensors for the complete movement information recording of the capture target. Results demonstrate that the developed system can accurately capture multiple moving targets and provide a higher recognition rate, reaching 75%∼100%. The maximum error of the system adopting the fusion target positioning algorithm is 10 cm, a reduction of 71.24% compared with that not using the fusion algorithm. The movements of different body parts are analyzed through example data. The recognition efficiency of “wave,” “crossover,” “pick things up,” “walk,” and “squat down” is as high as 100%. Hence, the proposed multiperson motion capture system that combines target positioning and inertial attitude sensing technology can provide better performance. The results are of great significance to promote the development of industries such as animation, medical care, games, and sports training.

Video based eye blink analysis for psychological state determination

The status of mental health and mood of human beings are well comprehensible by careful observation of movements of different body parts. Eye being the most prominent body part, analysis of different eye parameters such as blink, gaze, opening and closing rate provides important clues on mood status as well as mental health conditions. The present work can be viewed from a statistical and machine learning perspective that utilizes eye blink information to study the mental health status of a person. By using appropriate image processing techniques eye blinks of different subjects were collected through an experimental setup. The setup contained a recording environment where each participant was required to watch two videos of opposite emotions, i.e., joy and sad during different time settings. From the recorded videos of each participant, eye blinks were extracted and investigated. On analyzing the blink rates thoroughly, using statistical and machine learning means we observed; 1) an increase in number of eye blinks when the mood of a participant swings from sad to joy and 2) a significantly smaller number of blinks in depressed participants than the normal participants while in sad mood.

Estimation of Motion and Respiratory Characteristics during the Meditation Practice Based on Video Analysis.

Meditation practice is mental health training. It helps people to reduce stress and suppress negative thoughts. In this paper, we propose a camera-based meditation evaluation system, that helps meditators to improve their performance. We rely on two main criteria to measure the focus: the breathing characteristics (respiratory rate, breathing rhythmicity and stability), and the body movement. We introduce a contactless sensor to measure the respiratory rate based on a smartphone camera by detecting the chest keypoint at each frame, using an optical flow based algorithm to calculate the displacement between frames, filtering and de-noising the chest movement signal, and calculating the number of real peaks in this signal. We also present an approach to detecting the movement of different body parts (head, thorax, shoulders, elbows, wrists, stomach and knees). We have collected a non-annotated dataset for meditation practice videos consists of ninety videos and the annotated dataset consists of eight videos. The non-annotated dataset was categorized into beginner and professional meditators and was used for the development of the algorithm and for tuning the parameters. The annotated dataset was used for evaluation and showed that human activity during meditation practice could be correctly estimated by the presented approach and that the mean absolute error for the respiratory rate is around 1.75 BPM, which can be considered tolerable for the meditation application.

Uncoupling Between Multisensory Temporal Function and Nonverbal Turn-Taking in Autism Spectrum Disorder

The integration of information across distinct modalities enhances perceptual abilities. An ecologically important role of multisensory integration is in scaffolding verbal communication, which relies upon the precise temporal integration of auditory and visual cues. However, the role of (multi)sensory function in supporting another important aspect of communication, namely, nonverbal communication, is unknown. Here, individuals with autism spectrum disorder (ASD) and a group of typically developing (TD) participants performed a simultaneity judgment task to index their audiovisual temporal acuity for speech stimuli. Further, under a naturalistic scenario, nonverbal synchrony between the participant and a naive experimenter was measured. Automated motion analysis was performed to quantify movements of different body-parts. Results demonstrate a wider window of audiovisual temporal integration for ASD participants in comparison to their TD counterparts. Moreover, ASD individuals performed less complex movements and demonstrated less nonverbal synchrony during the interactive exchange. Lastly, multisensory temporal acuity significantly predicted the synchrony in hand and head movements between TD participants and the experimenter, but not between the ASD participants and the experimenter. Taken together, the results suggest an important role for multisensory perceptual abilities in shaping nonverbal communication between dyads and highlight the important role of perceptual systems in supporting social interactive skills.

Idiopathic generalized dystonia

Idiopathic generalized dystonia is a group of neurodegenerative diseases primarily charecterized by dystonic hyperkinetic disorder (irregular slow involuntary movements of different body parts accompanied by specific muscle tone changes and pathological poses). A 54-year-old female was admitted with various complaints. The leading syndrome was extrapyramidal due to which the differential diagnosis included Parkinson’s disease, multiple system atrophy, corticobasal degeneration, etc. The diagnosis of idiopathic generalized dystonia, in the form of lower extremity hyperkinesia with dystonic equinus of the left foot and hallux extension and cheirospasm, was made by a method of exclusion. The clinical case described in the article illustrates variety of clinical manifestations of the disease imitating clinical presentation of various neurological and psychiatric disorders, complexity of diagnostic search and importance of timely diagnosis of this disease.

Effect of insecticide treated nets fence in protecting cattle against tsetse and other biting flies in Arba Minch Zuria district, Southern Ethiopia

A field trial was carried out to assess the effect of insecticide treated net in protecting cattle from tsetse and other flies. A total of 35 pens were constructed, out of which 30 of them were fenced with insecticide treated net which served as treatment group and the remaining 5 pens were untreated controls. The fly populations around the pens were monthly monitored for five months using NGU traps deployed 5 m away from the cattle pens. The defensive movements of different body parts manifested by an animal for fly protections were observed for 5 minutes in each of the experimental and control groups. Additionally, other parameters such as packed cell volume, milk yield and body condition scores and buffy coat examination were investigated for both groups. Milk yield, body condition scores, packed cell volume (PCV) and data of defensive movements of animals were analyzed using linear model for longitudinal data or repeated measures by specifying time (monitoring cycles) and cattle as repeated variables. The result of this study showed that the overall proportion of fly catches was significantly lower in treated (38.3%) than control group (61.7%). Similarly, a significantly lower proportion of tsetse flies (28.4% versus 71.6%), biting flies (40.7% versus 59.3) and non-biting nuisance flies (39.7% versus 60.3%) compared to treatment. As a result, animals in treatment group had significantly lower average defensive movements of different body parts (7.84) compared to those in controls (16.37). All animals in both groups were negative for trypanosome infection and and there was no significant difference in their mean PCV values. Significant variation was not observed in daily milk yield between cows in treatment (0.83 liter) and in controls (0.53 liter). Fly densities had showed positive and negative relationships with defensive movements and PCV values over the monitoring time period, respectively. Body condition score of animals in the treatment group was also significantly higher (p<0.05) than those in controls. In conclusion, deltamethrin treated netting was found to reduce the challenges of tsetse and other biting flies, and thus can contribute to improved performances of animals in treatment groups.Keywords: Cattle; Fly protection; Insecticide treated net; Southern Ethiopia; Zero-grazing

Novel methodology for estimating Initial Contact events from accelerometers positioned at different body locations

Identifying Initial Contact events (ICE) is essential in gait analysis as they segment the walking pattern into gait cycles and facilitate the computation of other gait parameters. As such, numerous algorithms have been developed to identify ICE by placing the accelerometer at a specific body location. Simultaneously, many researchers have studied the effects of device positioning for participant or patient compliance, which is an important factor to consider especially for long-term studies in real-life settings. With the adoption of accelerometery for long-term gait analysis in daily living, current and future applications will require robust algorithms that can either autonomously adapt to changes in sensor positioning or can detect ICE from multiple sensors locations.This study presents a novel methodology that is capable of estimating ICE from accelerometers placed at different body locations. The proposed methodology, called DK-TiFA, is based on utilizing domain knowledge about the fundamental spectral relationships present between the movement of different body parts during gait to drive the time-frequency analysis of the acceleration signal. In order to assess the performance, DK-TiFA is benchmarked on four large publicly available gait databases, consisting of a total of 613 subjects and 7 unique body locations, namely, ankle, thigh, center waist, side waist, chest, upper arm and wrist. The DK-TiFA methodology is demonstrated to achieve high accuracy and robustness for estimating ICE from data consisting of different accelerometer specifications, varying gait speeds and different environments.

Vojta-Therapy

This paper proposed a novel computer vision-based framework to recognize the accurate movements of a patient during the Vojta-therapy. Vojta-therapy is a useful technique for the physical and mental impairments in humans. During the therapy, a specific stimulation is given to the patients to cause the patient's body to perform certain reflexive pattern movements. The repetition of this stimulation ultimately makes available the previously blocked connections between the spinal cord and brain, and after a few sessions, patients can perform these movements without any external stimulation. In this paper the authors propose an automatic method for patient detection and recognition of specific movements in his/her various body parts during the therapy process, using Microsoft Kinect camera. The proposed method works in three steps. In the first step, a robust template matching based algorithm is exploited for patient's detection using his/her head location. Second, several features are computed to capture the movements of different body parts during the therapy process. Third, in the classification stage, a multi-class support vector machine (mSVM) is used to classify the accurate movements of patient. The classification results ultimately reveal the correctness of the given treatment. The proposed algorithm is evaluated on the authors' challenging dataset, which was collected in a children hospital. The detection and classification results show that the proposed method is highly useful to recognize the correct movement pattern either in hospital or in-home therapy systems.

Neural pattern similarity between contra- and ipsilateral movements in high-frequency band of human electrocorticograms

The cortical motor areas are activated not only during contralateral limb movements but also during ipsilateral limb movements. Although these ipsilateral activities have been observed in several brain imaging studies, their functional role is poorly understood. Due to its high temporal resolution and low susceptibility to artifacts from body movements, the electrocorticogram (ECoG) is an advantageous measurement method for assessing the human brain function of motor behaviors. Here, we demonstrate that contra- and ipsilateral movements share a similarity in the high-frequency band of human ECoG signals. The ECoG signals were measured from the unilateral sensorimotor cortex while patients conducted self-paced movements of different body parts, contra- or ipsilateral to the measurement side. The movement categories (wrist, shoulder, or ankle) of ipsilateral movements were decoded as accurately as those of contralateral movements from spatial patterns of the high-frequency band of the precentral motor area (the primary motor and premotor areas). The decoder, trained in the high-frequency band of ipsilateral movements generalized to contralateral movements, and vice versa, confirmed that the activity patterns related to ipsilateral limb movements were similar to contralateral ones in the precentral motor area. Our results suggest that the high-frequency band activity patterns of ipsilateral and contralateral movements might be functionally coupled to control limbs, even during unilateral movements.

EP 111. Phase-locking analysis of EEG-data in movement related tasks reveals functional network of synchronous activity

The performance of motor actions is a highly complex task where the movement of different body parts has to be coordinated by the activity of various brain regions. In particular, the interplay of brain regions of the motor cortex is crucial. In the study presented here, the interaction of different motor related brain regions during simple internally and externally initiated finger movements was investigated during preparation and execution of those movements. To this end, EEG data (64 channel system) were recorded from 18 right-handed healthy participants (22–35 years, 10 female). The participants performed a finger tapping paradigm that contained left and right index finger movements which were triggered either by a visual cue or by voluntary choice. We carried out inter-regional phase-locking analysis of Morlet wavelet phases in delta-theta (2–7 Hz), alpha (8–12 Hz) and beta (13–30 Hz) frequency bands of the Laplacian referenced EEG data in order to identify coupling between brain regions during the motor task. We analyzed connectivity in a network involving electrodes lying above the premotor areas (PM: FC3, FC4), the supplementary motor areas (SMA: Cz, FCz) and the primary motor cortex (M1: C3, C4) as nodes. We found significant changes of synchronization in the delta-theta frequency band during both movement preparation and execution. The construction of lateralization networks revealed that the phase-locking effect in these frequency bands was stronger for connections from motor regions to supplementary motor areas contralaterally to the moving hand than on the ipsilateral side. The interregional synchronizations appeared only when both regions showed strong intraregional phase locking. Thus, intraregional phase locking in the delta-theta frequencies seems to be a prerequisite for interregional phase locking. We hypothesize that both intra- and interregional phase locking form a functional network of synchronous activity. This activity enhances the excitability of the motor system so that transient cue signals are able to induce different kinds of movements during movement preparation. Additionally we found strong synchronization in the beta-frequency band that appeared after the movement has been executed for connections from the supplementary motor areas to the primary motor cortex and the pre-motor cortex contralaterally to the moving hand. Since this synchronization effect is expressed significantly stronger during the self-initiated than during visually-triggered finger movements, we suggest that it might be related to the suppression of the internal “go” cue after the movement was executed.

Functional Diversification of Motor Neuron-specific Isl1 Enhancers during Evolution.

Functional diversification of motor neurons has occurred in order to selectively control the movements of different body parts including head, trunk and limbs. Here we report that transcription of Isl1, a major gene necessary for motor neuron identity, is controlled by two enhancers, CREST1 (E1) and CREST2 (E2) that allow selective gene expression of Isl1 in motor neurons. Introduction of GFP reporters into the chick neural tube revealed that E1 is active in hindbrain motor neurons and spinal cord motor neurons, whereas E2 is active in the lateral motor column (LMC) of the spinal cord, which controls the limb muscles. Genome-wide ChIP-Seq analysis combined with reporter assays showed that Phox2 and the Isl1-Lhx3 complex bind to E1 and drive hindbrain and spinal cord-specific expression of Isl1, respectively. Interestingly, Lhx3 alone was sufficient to activate E1, and this may contribute to the initiation of Isl1 expression when progenitors have just developed into motor neurons. E2 was induced by onecut 1 (OC-1) factor that permits Isl1 expression in LMCm neurons. Interestingly, the core region of E1 has been conserved in evolution, even in the lamprey, a jawless vertebrate with primitive motor neurons. All E1 sequences from lamprey to mouse responded equally well to Phox2a and the Isl1-Lhx3 complex. Conversely, E2, the enhancer for limb-innervating motor neurons, was only found in tetrapod animals. This suggests that evolutionarily-conserved enhancers permit the diversification of motor neurons.

The postcentral sulcal complex and the transverse postcentral sulcus and their relation to sensorimotor functional organization.

It has been demonstrated that the postcentral sulcus, which forms the posterior boundary of the sensorimotor region, is a complex of distinct sulcal segments. Although the general somatotopic arrangement in the human sensorimotor cortex is relatively well known, we do not know whether the different segments of the postcentral sulcus relate in a systematic way to the sensorimotor functional representations. Participants were scanned with functional magnetic resonance imaging while they made movements of different body parts and the location of functional activity was examined on a subject-by-subject basis with respect to the morphological features of the postcentral sulcus. The findings demonstrate that the postcentral sulcus of each subject may be divided into five segments and there is a tight relationship between sensorimotor representations of different body parts and specific segments of the postcentral sulcus. The results also addressed the issue of the transverse postcentral sulcus, a short sulcus that is present within the ventral part of the postcentral gyrus in some brains. It was shown that, when present, this sulcus is functionally related to the oral (mouth and tongue) sensorimotor representation. When this sulcus is not present, the inferior postcentral sulcus which is also related to the oral representation is longer. Thus, the sulcal morphology provides an improved framework for functional assignments in individual subjects.

EEG resolutions in detecting and decoding finger movements from spectral analysis.

Mu/beta rhythms are well-studied brain activities that originate from sensorimotor cortices. These rhythms reveal spectral changes in alpha and beta bands induced by movements of different body parts, e.g., hands and limbs, in electroencephalography (EEG) signals. However, less can be revealed in them about movements of different fine body parts that activate adjacent brain regions, such as individual fingers from one hand. Several studies have reported spatial and temporal couplings of rhythmic activities at different frequency bands, suggesting the existence of well-defined spectral structures across multiple frequency bands. In the present study, spectral principal component analysis (PCA) was applied on EEG data, obtained from a finger movement task, to identify cross-frequency spectral structures. Features from identified spectral structures were examined in their spatial patterns, cross-condition pattern changes, detection capability of finger movements from resting, and decoding performance of individual finger movements in comparison to classic mu/beta rhythms. These new features reveal some similar, but more different spatial and spectral patterns as compared with classic mu/beta rhythms. Decoding results further indicate that these new features (91%) can detect finger movements much better than classic mu/beta rhythms (75.6%). More importantly, these new features reveal discriminative information about movements of different fingers (fine body-part movements), which is not available in classic mu/beta rhythms. The capability in decoding fingers (and hand gestures in the future) from EEG will contribute significantly to the development of non-invasive BCI and neuroprosthesis with intuitive and flexible controls.

Hierarchical control of two-dimensional gaze saccades

Coordinating the movements of different body parts is a challenging process for the central nervous system because of several problems. Four of these main difficulties are: first, moving one part can move others; second, the parts can have different dynamics; third, some parts can have different motor goals; and fourth, some parts may be perturbed by outside forces. Here, we propose a novel approach for the control of linked systems with feedback loops for each part. The proximal parts have separate goals, but critically the most distal part has only the common goal. We apply this new control policy to eye-head coordination in two-dimensions, specifically head-unrestrained gaze saccades. Paradoxically, the hierarchical structure has controllers for the gaze and the head, but not for the eye (the most distal part). Our simulations demonstrate that the proposed control structure reproduces much of the published empirical data about gaze movements, e.g., it compensates for perturbations, accurately reaches goals for gaze and head from arbitrary initial positions, simulates the nine relationships of the head-unrestrained main sequence, and reproduces observations from lesion and single-unit recording experiments. We conclude by showing how our model can be easily extended to control structures with more linked segments, such as the control of coordinated eye on head on trunk movements.

What Body Parts Reveal about the Organization of the Brain

In this issue of Neuron, Orlov etal. show that the human occipitotemporal cortex contains regions responding preferentially to body part categories, such as upper limbs (hand, elbow), torsos, or lower faces (mouth, chin). This organization may reflect differences in the connectivity of these regions with other brain regions, to support the efficient processing of the different types of information different body parts provide.

Pain in older persons with severe dementia. Psychometric properties of the Mobilization–Observation–Behaviour–Intensity–Dementia (MOBID‐2) Pain Scale in a clinical setting

To assess pain in older persons with severe dementia is a challenge due to reduced self-report capacity. Recently, the development and psychometric property testing of the Mobilization-Observation-Behaviour-Intensity-Dementia (MOBID) Pain Scale was described using video-recording. The purpose of this article was to present the further development of this instrument. In MOBID-2 Pain Scale, the assessment of inferred pain intensity is based on patient's pain behaviours in connection with standardized, guided movements of different body parts (Part 1). In addition, MOBID-2 includes the observation of pain behaviours related to internal organs, head and skin registered on pain drawings and monitored over time (Part 2). The aim of this study was to examine psychometric properties of the MOBID-2 Pain Scale, like inter-rater and test-retest reliability, internal consistency, as well as face-, construct- and concurrent validity. Patients with severe dementia (n = 77) were examined by 28 primary caregivers in clinical practice, who concurrently and independently completed the MOBID-2 Pain Scale. Characteristics of the patients' pain were also investigated by their physicians (n = 4). Prevalence of any pain was 81%, with predominance to the musculoskeletal system, highly associated with the MOBID-2 overall pain score (rho = 0.82). Most frequent and painful were mobilizing legs. Pain in pelvis and/or genital organs was frequently observed. Moderate to excellent agreement was demonstrated for behaviours and pain drawings (kappa = 0.41-0.90 and kappa = 0.46-0.93). Inter-rater and test-retest reliability for pain intensity was very good, ICC (1, 1) ranging 0.80-0.94 and 0.60-0.94. Internal consistency was highly satisfactory; Cronbach's alpha ranging 0.82-0.84. Face-, construct- and concurrent validity was good. Overall pain intensity by MOBID-2 was well correlated with physicians' clinical examination and defined pain variables (rho = 0.41-0.64). On the basis of pain behaviours, standardized movements and pain drawings, MOBID-2 Pain Scale was shown to be sufficiently reliable, valid and time-effective for nurses to assess pain in patients with severe dementia.