Physical Factors Associated with Non-Specific Neck Pain: Correlations Among Pain, Disability, Posture, Endurance, and Compensatory Movement.

BACKGROUND This study was conducted to investigate physical risk factors in patients with non-specific neck pain. The correlations among pain intensity, pressure pain threshold, range of motion (ROM), and disability index were analyzed in 50 patients with non-specific neck pain at a hospital in Korea. MATERIAL AND METHODS We enrolled 50 patients diagnosed with non-specific neck pain by a doctor. All subjects were evaluated for pain intensity, pressure threshold, degree of disability, active range of motion (ROM) of the neck, upper cervical rotation ROM, muscular endurance of deep cervical flexor, compensatory movements for neck flexion, forward head posture, shoulder height difference, and rounded shoulder posture. The correlation between each variable was analyzed. RESULTS Pain intensity had a significant correlation between cervical rotation ROM, cervical flexion-rotation ROM, rounded shoulder posture, shoulder height difference, and forward head posture (P<.05). There was a significant correlation between the pressure pain threshold and the cervical extension ROM, cervical flexion-rotation ROM, and rounded shoulder height (P<.05). The disability index had a significant correlation between the cervical rotation ROM, cervical flexion-rotation ROM, rounded shoulder posture, and the compensatory movement of neck flexion (P<.05). CONCLUSIONS Physical risk factors for non-specific neck pain included cervical rotation ROM, upper cervical rotation ROM, rounded shoulder posture, shoulder height difference, and cervical flexion compensatory movements, which can affect pain intensity and pressure pain threshold.

Age-related changes in cheek skin movement: A case study of Japanese women.

BACKGROUND: The majority of conventional studies on skin aging have focused on static conditions. However, in daily life, the facial skin we encounter is constantly in motion due to conversational expressions and changes in facial expressions, causing the skin to alter its position and shape, resulting in a dynamic state. Consequently, it is hypothesized that characteristics of aging not apparent in static conditions may be present in the dynamic state of the skin. Therefore, this study investigates age-related changes in dynamic skin characteristics associated with facial expression alterations. METHODS: A motion capture system measured the dynamic characteristics (delay and stretchiness of skin movement associated with expression) of the cheek skin in response to facial expressions among 86 Japanese women aged between 20 and 69 years. RESULTS: The findings revealed an increase in the delay of cheek skin response to facial expressions (r = 0.24, p < 0.05) and a decrease in the stretchiness of the lower cheek area with age (r = 0.60, p < 0.01). An increasing variance in delay and stretchiness within the same age group was also observed with aging. CONCLUSION: The findings of this study revealed that skin aging encompasses both static characteristics, such as spots, wrinkles, and sagging, traditionally studied in aging research, and dynamic aging characteristics of the skin that emerge in response to facial expression changes. These dynamic aging characteristics could pave the way for the development of new methodologies in skin aging analysis and potentially improve our understanding and treatment of aging impressions that are visually perceptible in daily life but remain unexplored.

IMU Data-Driven and PCA-Based Approach to Establish Quantifiable and Practically Applicable Measures for V2 Technique Elements in Cross-Country Skiing.

Quantifying movement coordination in cross-country (XC) skiing, specifically the technique with its elemental forms, is challenging. Particularly, this applies when trying to establish a bidirectional transfer between scientific theory and practical experts' knowledge as expressed, for example, in ski instruction curricula. The objective of this study was to translate 14 curricula-informed distinct elements of the V2 ski-skating technique (horizontal and vertical posture, lateral tilt, head position, upper body rotation, arm swing, shoulder abduction, elbow flexion, hand and leg distance, plantar flexion, ski set-down, leg push-off, and gliding phase) into plausible, valid and applicable measures to make the technique training process more quantifiable and scientifically grounded. Inertial measurement unit (IMU) data of 10 highly experienced XC skiers who demonstrated the technique elements by two extreme forms each (e.g., anterior versus posterior positioning for the horizontal posture) were recorded. Element-specific principal component analyses (PCAs)-driven by the variance produced by the technique extremes-resulted in movement components that express quantifiable measures of the underlying technique elements. Ten measures were found to be sensitive in distinguishing between the inputted extreme variations using statistical parametric mapping (SPM), whereas for four elements the SPM did not detect differences (lateral tilt, plantar flexion, ski set-down, and leg push-off). Applicability of the established technique measures was determined based on quantifying individual techniques through them. The study introduces a novel approach to quantitatively assess V2 ski-skating technique, which might help to enhance technique feedback and bridge the communication gap that often exists between practitioners and scientists.

A Review of Motor Brain-Computer Interfaces Using Intracranial Electroencephalography Based on Surface Electrodes and Depth Electrodes.

Brain-computer interfaces (BCIs) provide a communication interface between the brain and external devices and have the potential to restore communication and control in patients with neurological injury or disease. For the invasive BCIs, most studies recruited participants from hospitals requiring invasive device implantation. Three widely used clinical invasive devices that have the potential for BCIs applications include surface electrodes used in electrocorticography (ECoG) and depth electrodes used in Stereo-electroencephalography (SEEG) and deep brain stimulation (DBS). This review focused on BCIs research using surface (ECoG) and depth electrodes (including SEEG, and DBS electrodes) for movement decoding on human subjects. Unlike previous reviews, the findings presented here are from the perspective of the decoding target or task. In detail, five tasks will be considered, consisting of the kinematic decoding, kinetic decoding,identification of body parts, dexterous hand decoding, and motion intention decoding. The typical studies are surveyed and analyzed. The reviewed literature demonstrated a distributed motor-related network that spanned multiple brain regions. Comparison between surface and depth studies demonstrated that richer information can be obtained using surface electrodes. With regard to the decoding algorithms, deep learning exhibited superior performance using raw signals than traditional machine learning algorithms. Despite the promising achievement made by the open-loop BCIs, closed-loop BCIs with sensory feedback are still in their early stage, and the chronic implantation of both ECoG surface and depth electrodes has not been thoroughly evaluated.

Artificial intelligence detects awareness of functional relation with the environment in 3 month old babies.

A recent experiment probed how purposeful action emerges in early life by manipulating infants' functional connection to an object in the environment (i.e., tethering an infant's foot to a colorful mobile). Vicon motion capture data from multiple infant joints were used here to create Histograms of Joint Displacements (HJDs) to generate pose-based descriptors for 3D infant spatial trajectories. Using HJDs as inputs, machine and deep learning systems were tasked with classifying the experimental state from which snippets of movement data were sampled. The architectures tested included k-Nearest Neighbour (kNN), Linear Discriminant Analysis (LDA), Fully connected network (FCNet), 1D-Convolutional Neural Network (1D-Conv), 1D-Capsule Network (1D-CapsNet), 2D-Conv and 2D-CapsNet. Sliding window scenarios were used for temporal analysis to search for topological changes in infant movement related to functional context. kNN and LDA achieved higher classification accuracy with single joint features, while deep learning approaches, particularly 2D-CapsNet, achieved higher accuracy on full-body features. For each AI architecture tested, measures of foot activity displayed the most distinct and coherent pattern alterations across different experimental stages (reflected in the highest classification accuracy rate), indicating that interaction with the world impacts the infant behaviour most at the site of organism~world connection.

Awareness of embodiment enhances enjoyment and engages sensorimotor cortices.

Whether in performing arts, sporting, or everyday contexts, when we watch others move, we tend to enjoy bodies moving in synchrony. Our enjoyment of body movements is further enhanced by our own prior experience with performing those movements, or our 'embodied experience'. The relationships between movement synchrony and enjoyment, as well as embodied experience and movement enjoyment, are well known. The interaction between enjoyment of movements, synchrony, and embodiment is less well understood, and may be central for developing new approaches for enriching social interaction. To examine the interplay between movement enjoyment, synchrony, and embodiment, we asked participants to copy another person's movements as accurately as possible, thereby gaining embodied experience of movement sequences. Participants then viewed other dyads performing the same or different sequences synchronously, and we assessed participants' recognition of having performed these sequences, as well as their enjoyment of each movement sequence. We used functional near-infrared spectroscopy to measure cortical activation over frontotemporal sensorimotor regions while participants performed and viewed movements. We found that enjoyment was greatest when participants had mirrored the sequence and recognised it, suggesting that awareness of embodiment may be central to enjoyment of synchronous movements. Exploratory analyses of relationships between cortical activation and enjoyment and recognition implicated the sensorimotor cortices, which subserve action observation and aesthetic processing. These findings hold implications for clinical research and therapies seeking to foster successful social interaction.

Wireless Mouth Motion Recognition System Based on EEG-EMG Sensors for Severe Speech Impairments.

This study aims to demonstrate the feasibility of using a new wireless electroencephalography (EEG)-electromyography (EMG) wearable approach to generate characteristic EEG-EMG mixed patterns with mouth movements in order to detect distinct movement patterns for severe speech impairments. This paper describes a method for detecting mouth movement based on a new signal processing technology suitable for sensor integration and machine learning applications. This paper examines the relationship between the mouth motion and the brainwave in an effort to develop nonverbal interfacing for people who have lost the ability to communicate, such as people with paralysis. A set of experiments were conducted to assess the efficacy of the proposed method for feature selection. It was determined that the classification of mouth movements was meaningful. EEG-EMG signals were also collected during silent mouthing of phonemes. A few-shot neural network was trained to classify the phonemes from the EEG-EMG signals, yielding classification accuracy of 95%. This technique in data collection and processing bioelectrical signals for phoneme recognition proves a promising avenue for future communication aids.

An Overall Automated Architecture Based on the Tapping Test Measurement Protocol: Hand Dexterity Assessment through an Innovative Objective Method.

The present work focuses on the tapping test, which is a method that is commonly used in the literature to assess dexterity, speed, and motor coordination by repeatedly moving fingers, performing a tapping action on a flat surface. During the test, the activation of specific brain regions enhances fine motor abilities, improving motor control. The research also explores neuromuscular and biomechanical factors related to finger dexterity, revealing neuroplastic adaptation to repetitive movements. To give an objective evaluation of all cited physiological aspects, this work proposes a measurement architecture consisting of the following: (i) a novel measurement protocol to assess the coordinative and conditional capabilities of a population of participants; (ii) a suitable measurement platform, consisting of synchronized and non-invasive inertial sensors to be worn at finger level; (iii) a data analysis processing stage, able to provide the final user (medical doctor or training coach) with a plethora of useful information about the carried-out tests, going far beyond state-of-the-art results from classical tapping test examinations. Particularly, the proposed study underscores the importance interdigital autonomy for complex finger motions, despite the challenges posed by anatomical connections; this deepens our understanding of upper limb coordination and the impact of neuroplasticity, holding significance for motor abilities assessment, improvement, and therapeutic strategies to enhance finger precision. The proof-of-concept test is performed by considering a population of college students. The obtained results allow us to consider the proposed architecture to be valuable for many application scenarios, such as the ones related to neurodegenerative disease evolution monitoring.

Comparison of Six Sensor Fusion Algorithms with Electrogoniometer Estimation of Wrist Angle in Simulated Work Tasks.

Hand-intensive work is strongly associated with work-related musculoskeletal disorders (WMSDs) of the hand/wrist and other upper body regions across diverse occupations, including office work, manufacturing, services, and healthcare. Addressing the prevalence of WMSDs requires reliable and practical exposure measurements. Traditional methods like electrogoniometry and optical motion capture, while reliable, are expensive and impractical for field use. In contrast, small inertial measurement units (IMUs) may provide a cost-effective, time-efficient, and user-friendly alternative for measuring hand/wrist posture during real work. This study compared six orientation algorithms for estimating wrist angles with an electrogoniometer, the current gold standard in field settings. Six participants performed five simulated hand-intensive work tasks (involving considerable wrist velocity and/or hand force) and one standardised hand movement. Three multiplicative Kalman filter algorithms with different smoothers and constraints showed the highest agreement with the goniometer. These algorithms exhibited median correlation coefficients of 0.75-0.78 for flexion/extension and 0.64 for radial/ulnar deviation across the six subjects and five tasks. They also ranked in the top three for the lowest mean absolute differences from the goniometer at the 10th, 50th, and 90th percentiles of wrist flexion/extension (9.3°, 2.9°, and 7.4°, respectively). Although the results of this study are not fully acceptable for practical field use, especially for some work tasks, they indicate that IMU-based wrist angle estimation may be useful in occupational risk assessments after further improvements.

Tai Chi Movement Recognition and Precise Intervention for the Elderly Based on Inertial Measurement Units and Temporal Convolutional Neural Networks.

(1) Background: The objective of this study was to recognize tai chi movements using inertial measurement units (IMUs) and temporal convolutional neural networks (TCNs) and to provide precise interventions for elderly people. (2) Methods: This study consisted of two parts: firstly, 70 skilled tai chi practitioners were used for movement recognition; secondly, 60 elderly males were used for an intervention study. IMU data were collected from skilled tai chi practitioners performing Bafa Wubu, and TCN models were constructed and trained to classify these movements. Elderly participants were divided into a precision intervention group and a standard intervention group, with the former receiving weekly real-time IMU feedback. Outcomes measured included balance, grip strength, quality of life, and depression. (3) Results: The TCN model demonstrated high accuracy in identifying tai chi movements, with percentages ranging from 82.6% to 94.4%. After eight weeks of intervention, both groups showed significant improvements in grip strength, quality of life, and depression. However, only the precision intervention group showed a significant increase in balance and higher post-intervention scores compared to the standard intervention group. (4) Conclusions: This study successfully employed IMU and TCN to identify Tai Chi movements and provide targeted feedback to older participants. Real-time IMU feedback can enhance health outcome indicators in elderly males.

Three-Dimensional Human Posture Recognition by Extremity Angle Estimation with Minimal IMU Sensor.

Recently, posture recognition technology has advanced rapidly. Herein, we present a novel posture angle calculation system utilizing a single inertial measurement unit and a spatial geometric equation to accurately identify the three-dimensional (3D) motion angles and postures of both the upper and lower limbs of the human body. This wearable system facilitates continuous monitoring of body movements without the spatial limitations or occlusion issues associated with camera-based methods. This posture-recognition system has many benefits. Providing precise posture change information helps users assess the accuracy of their movements, prevent sports injuries, and enhance sports performance. This system employs a single inertial sensor, coupled with a filtering mechanism, to calculate the sensor's trajectory and coordinates in 3D space. Subsequently, the spatial geometry equation devised herein accurately computed the joint angles for changing body postures. To validate its effectiveness, the joint angles estimated from the proposed system were compared with those from dual inertial sensors and image recognition technology. The joint angle discrepancies for this system were within 10° and 5° when compared with dual inertial sensors and image recognition technology, respectively. Such reliability and accuracy of the proposed angle estimation system make it a valuable reference for assessing joint angles.

Top-down and bottom-up oscillatory dynamics regulate implicit visuomotor sequence learning.

Implicit visuomotor sequence learning is crucial for acquiring skills that result in automated behaviors. The oscillatory dynamics underpinning this learning process are not well understood. To address this gap, the current study employed electroencephalography with a medium-density array (64 electrodes) to investigate oscillatory activity associated with implicit visuomotor sequence learning in the Serial Reaction Time task. In the task, participants unknowingly learn a series of finger movements. Eighty-five healthy adults participated in the study. Analyses revealed that theta activity at the vertex and alpha/beta activity over the motor areas decreased over the course of learning. No associations between alpha/beta and theta power were observed. These findings are interpreted within a dual-process framework: midline theta activity is posited to regulate top-down attentional processes, whereas beta activity from motor areas underlies the bottom-up encoding of sensory information from movement. From this model, we suggest that during implicit visuomotor sequence learning, top-down processes become disengaged (indicated by a reduction in theta activity), and modality specific bottom-up processes encode the motor sequence (indicated by a reduction in alpha/beta activity).

Pink noise promotes sooner state transitions during bimanual coordination.

The seemingly straightforward task of tying one's shoes requires a sophisticated interplay of joints, muscles, and neural pathways, posing a formidable challenge for researchers studying the intricacies of coordination. A widely accepted framework for measuring coordinated behavior is the Haken-Kelso-Bunz (HKB) model. However, a significant limitation of this model is its lack of accounting for the diverse variability structures inherent in the coordinated systems it frequently models. Variability is a pervasive phenomenon across various biological and physical systems, and it changes in healthy adults, older adults, and pathological populations. Here, we show, both empirically and with simulations, that manipulating the variability in coordinated movements significantly impacts the ability to change coordination patterns-a fundamental feature of the HKB model. Our results demonstrate that synchronized bimanual coordination, mirroring a state of healthy variability, instigates earlier transitions of coordinated movements compared to other variability conditions. This suggests a heightened adaptability when movements possess a healthy variability. We anticipate our study to show the necessity of adapting the HKB model to encompass variability, particularly in predictive applications such as neuroimaging, cognition, skill development, biomechanics, and beyond.

Comparing and characterizing scapular muscle activation ratios in males and females during execution of common functional movements.

Background: The shoulder complex relies on scapular movement controlled by periscapular muscles for optimal arm function. However, minimal research has explored scapular muscle activation ratios during functional tasks, nor how they might be influenced by biological sex. This investigation aims to characterize how sex impacts scapular muscle activation ratios during functional tasks. Methods: Twenty participants (ten females, ten males) were assessed with surface electromyography (EMG) and motion tracking during seven functional tasks. Activation ratios were calculated from normalized EMG for the three trapezius muscles and serratus anterior. Scapular angles were calculated using a YXZ Euler sequence. Two-way mixed methods ANOVAs (p < .05) were used to assess the effects of sex and humeral elevation level on ratios and angles. Results: Sex-based differences were present in the Tie Apron task, with males exhibiting higher upper trapezius/lower trapezius and upper trapezius/middle trapezius ratios than females. Males also demonstrated decreased internal rotation in this task. Other tasks showcased significant sex-based differences in scapular upward rotation but not in activation ratios. Humeral elevation generally demonstrated an inverse relationship with scapular muscle activation ratios. Conclusions: This study highlights sex-based differences in scapular muscle activation ratios during specific functional tasks, emphasizing the need to consider sex in analyses of shoulder movements. Normative activation ratios for functional tasks were provided, offering a foundation for future comparisons with non-normative groups. Further research is warranted to confirm and explore additional influencing factors, advancing our understanding of shoulder activation and movement in diverse populations.

Neck Kinematics in Patients With Chronic Mechanical Neck Pain: An Observational Study to Explore the Integration of Multiple Influencing Factors Through a Bayesian Model-Based Approach.

The aim of this observational, cross-sectional study is to evaluate potential differences in kinematics, specifically range of motion (ROM) and velocity, during planar cervical movements between patients with non-traumatic chronic neck pain and disability and asymptomatic controls, while accounting for potential influencing variables of age, sex and fear of movement. The influence of pain intensity, neck disability, age, sex or fear of motion on kinematics was analyzed through robust multivariate Bayesian regression models fitted using the brms library in R. Forty-three patients with neck pain (aged 36.70 ± 13.75 years; 10 men and 33 women) and 42 asymptomatic participants (aged 32.74 ± 13.24 years; 25 men and 17 women) completed the study protocol. The presence of neck pain/disability was associated with lower ROM and peak velocity during all planar movements when considering the influence of age, sex or fear of motion, with standardized regression coefficients that had a small effect size (ranged from 0.11 to 0.28) and estimated differences of less than 2.21° in ROM and 25.61°/s in peak velocity. Although patients with chronic mechanical neck pain showed reduced ROM and peak velocity, the small effect sizes and the low estimated differences between groups question the relevance and clinical usefulness of kinematic analysis of planar movements in samples of patients similar to those included in our study. It is probable that there are differences between the groups, but it is insufficient to rely solely on kinematic variables for patient discrimination. This limitation likely arises from the substantial variability in patient kinematics.

Concerto of movement: how expertise shapes the synergistic control of upper limb muscles in complex motor tasks with varying tempo and dynamics.

Objective. This research aims to reveal how the synergistic control of upper limb muscles adapts to varying requirements in complex motor tasks and how expertise shapes the motor modules.Approach. We study the muscle synergies of a complex, highly skilled and flexible task-piano playing-and characterize expertise-related muscle-synergy control that permits the experts to effortlessly execute the same task at different tempo and force levels. Surface EMGs (28 muscles) were recorded from adult novice (N= 10) and expert (N= 10) pianists as they played scales and arpeggios at different tempo-force combinations. Muscle synergies were factorized from EMGs.Main results. We found that experts were able to cover both tempo and dynamic ranges using similar synergy selections and achieved better performance, while novices altered synergy selections more to adapt to the changing tempi and keystroke intensities compared with experts. Both groups relied on fine-tuning the muscle weights within specific synergies to accomplish the different task styles, while the experts could tune the muscles in a greater number of synergies, especially when changing the tempo, and switch tempo over a wider range.Significance. Our study sheds light on the control mechanism underpinning expertise-related motor flexibility in highly skilled motor tasks that require decade-long training. Our results have implications on musical and sports training, as well as motor prosthetic design.

Developing a device for simultaneously investigating pivoting neuromuscular control and muscle properties toward a multi-axis rehabilitation.

Understanding the pivoting neuromuscular control of the lower limb and its associated muscle properties is critical for developing diagnostic and rehabilitation tools. However, to the best of our knowledge, a device that can evaluate these factors simultaneously remains lacking. To address this gap, a device that can investigate pivoting neuromuscular control and associated muscle properties was developed in this study. The proposed device consisted of a pivoting mechanism and height-adjustable chair with a brace interface. The device can control a footplate at various speeds to facilitate pivoting stretching and quantify neuromuscular control. Time-synchronized ultrasonographic images can be acquired simultaneously to quantify muscle properties during both active and passive pivoting movements. The muscle displacement, fascicle length/displacement, pennation angle, pivoting stiffness, and pivoting instability were investigated using the proposed device. Further, the feasibility of the device was demonstrated through a cross-sectional study with healthy subjects. The proposed device successfully quantified changes in muscle displacement during passive and active pivoting movements, pivoting stiffness during passive movements, and neuromuscular control during active movements. Therefore, the proposed device is expected to be used as a research and therapeutic tool for improving pivoting neuromuscular control and muscle functions and investigating the underlying mechanisms associated between muscle properties and joint movement in the transverse plane.

Development of full-body rhythmic synchronization in middle childhood.

Rhythmic entrainment is a fundamental aspect of musical behavior, but the skills required to accurately synchronize movement to the beat seem to develop over many years. Motion capture studies of corporeal synchronization have shown immature abilities to lock in to the beat in children before age 5, and reliable synchronization ability in adults without musical training; yet there is a lack of data on full-body synchronization skills between early childhood and adulthood. To document typical rhythmic synchronization during middle childhood, we used a wireless motion capture device to measure period- and phase-locking of full body movement to rhythm and metronome stimuli in 6 to 11 year-old children in comparison with adult data. Results show a gradual improvement with age; however children's performance did not reach adult levels by age 12, suggesting that these skills continue to develop during adolescence. Our results suggest that in the absence of specific music training, full-body rhythmic entrainment skills improve gradually during middle childhood, and provide metrics for examining the continued maturation of these skills during adolescence.

Understanding the flexion-relaxation phenomenon in non-specific chronic low back pain patients throught immersive virtual reality feedback approach.

The flexion-relaxation phenomenon (FRP) is frequently absent among non-specific chronic low back pain (NSCLBP) patients. However, it is unknown whether this absence is intrinsic to their pathology or merely a consequence of reduced trunk flexion. Immersive virtual reality (IVR) can create a patient avatar whose range of motion can be modulated to differ from the real movement. The present study enrolled 15 NSCLBP patients and 15 asymptomatic participants with similar characteristics to disentangle the relationship between range of motion and the FRP in NSCLBP using IVR. Trunk kinematics and lumbar muscle electromyography were assessed. The IVR environment was combined with a motion capture system to create avatars that moved like each participant. The IVR display showed a closed room and a mirror reflecting the subject's avatar with a target line to be reached by trunk flexion. The avatar's trunk movements were modulated from reality, leading the participants to flex their trunk more than their voluntary maximum trunk flexion. Under IVR conditions, NSCLBP patients significantly increased their trunk flexion angle, which was coupled with a significant improvement in the FRP. The absence of the FRP among the NSCLBP population appeared to be primarily related to reduced trunk flexion.

Stretchable glove for accurate and robust hand pose reconstruction based on comprehensive motion data.

We propose a compact wearable glove capable of estimating both the finger bone lengths and the joint angles of the wearer with a simple stretch-based sensing mechanism. The soft sensing glove is designed to easily stretch and to be one-size-fits-all, both measuring the size of the hand and estimating the finger joint motions of the thumb, index, and middle fingers. The system was calibrated and evaluated using comprehensive hand motion data that reflect the extensive range of natural human hand motions and various anatomical structures. The data were collected with a custom motion-capture setup and transformed into the joint angles through our post-processing method. The glove system is capable of reconstructing arbitrary and even unconventional hand poses with accuracy and robustness, confirmed by evaluations on the estimation of bone lengths (mean error: 2.1 mm), joint angles (mean error: 4.16°), and fingertip positions (mean 3D error: 4.02 mm), and on overall hand pose reconstructions in various applications. The proposed glove allows us to take advantage of the dexterity of the human hand with potential applications, including but not limited to teleoperation of anthropomorphic robot hands or surgical robots, virtual and augmented reality, and collection of human motion data.