A Serious Game for the Assessment of Visuomotor Adaptation Capabilities during Locomotion Tasks Employing an Embodied Avatar in Virtual Reality.

The study of visuomotor adaptation (VMA) capabilities has been encompassed in various experimental protocols aimed at investigating human motor control strategies and/or cognitive functions. VMA-oriented frameworks can have clinical applications, primarily in the investigation and assessment of neuromotor impairments caused by conditions such as Parkinson's disease or post-stroke, which affect the lives of tens of thousands of people worldwide. Therefore, they can enhance the understanding of the specific mechanisms of such neuromotor disorders, thus being a potential biomarker for recovery, with the aim of being integrated with conventional rehabilitative programs. Virtual Reality (VR) can be entailed in a framework targeting VMA since it allows the development of visual perturbations in a more customizable and realistic way. Moreover, as has been demonstrated in previous works, a serious game (SG) can further increase engagement thanks to the use of full-body embodied avatars. Most studies implementing VMA frameworks have focused on upper limb tasks and have utilized a cursor as visual feedback for the user. Hence, there is a paucity in the literature about VMA-oriented frameworks targeting locomotion tasks. In this article, the authors present the design, development, and testing of an SG-based framework that addresses VMA in a locomotion activity by controlling a full-body moving avatar in a custom VR environment. This workflow includes a set of metrics to quantitatively assess the participants' performance. Thirteen healthy children were recruited to evaluate the framework. Several quantitative comparisons and analyses were run to validate the different types of introduced visuomotor perturbations and to evaluate the ability of the proposed metrics to describe the difficulty caused by such perturbations. During the experimental sessions, it emerged that the system is safe, easy to use, and practical in a clinical setting. Despite the limited sample size, which represents the main limitation of the study and can be compensated for with future recruitment, the authors claim the potential of this framework as a useful instrument for quantitatively assessing either motor or cognitive impairments. The proposed feature-based approach gives several objective parameters as additional biomarkers that can integrate the conventional clinical scores. Future studies might investigate the relation between the proposed biomarkers and the clinical scores for specific disorders such as Parkinson's disease and cerebral palsy.

Age estimation by palatal suture using modified Kamijo's method.

The present study aimed to investigate the correlation between palatal suture obliteration and age in modern Japanese and to develop an age estimation equation by modifying Kamijo's (1949) method. The subjects were 195 Japanese skeletal remains (155 males and 40 females) whose age and sex were known. First, obliteration score (OS) was obtained by measuring palatal suture obliteration from photographic images taken at the time of forensic autopsy, and the correlation with age was examined; no significant correlation was found in females. Second, the palatal sutures were divided into 14 sections, and each section was scored from 0 to 4 points according to the degree of the suture obliteration. Suture scores (SS) were then calculated for each of the four sutures, and the sum of the 14 scores (TSS: total suture score) was used to perform regression analysis for age. For male and all subjects (male and female), age significantly increased (p < 0.001) according to increment of SSs for all sutures. TSS has the highest regression coefficient (r = 0.540), and the lowest standard error of estimation (13.54 years) for all of the patients. The intra- and inter-observer agreement scoring showed high reliability. Validation study using the formulae showed a high percentage of correct responses (80 %). In conclusion, age estimation regression formula by palatal suture using modified Kamijo's method was established for Japanese population, and the study showed the formula might be valid for age estimation.

BERT for Activity Recognition Using Sequences of Skeleton Features and Data Augmentation with GAN.

Recently, the scientific community has placed great emphasis on the recognition of human activity, especially in the area of health and care for the elderly. There are already practical applications of activity recognition and unusual conditions that use body sensors such as wrist-worn devices or neck pendants. These relatively simple devices may be prone to errors, might be uncomfortable to wear, might be forgotten or not worn, and are unable to detect more subtle conditions such as incorrect postures. Therefore, other proposed methods are based on the use of images and videos to carry out human activity recognition, even in open spaces and with multiple people. However, the resulting increase in the size and complexity involved when using image data requires the use of the most recent advanced machine learning and deep learning techniques. This paper presents an approach based on deep learning with attention to the recognition of activities from multiple frames. Feature extraction is performed by estimating the pose of the human skeleton, and classification is performed using a neural network based on Bidirectional Encoder Representation of Transformers (BERT). This algorithm was trained with the UP-Fall public dataset, generating more balanced artificial data with a Generative Adversarial Neural network (GAN), and evaluated with real data, outperforming the results of other activity recognition methods using the same dataset.

Skeleton-Based Human Pose Recognition Using Channel State Information: A Survey.

With the increasing demand for human-computer interaction and health monitoring, human behavior recognition with device-free patterns has attracted extensive attention. The fluctuations of the Wi-Fi signal caused by human actions in a Wi-Fi coverage area can be used to precisely identify the human skeleton and pose, which effectively overcomes the problems of the traditional solution. Although many promising results have been achieved, no survey summarizes the research progress. This paper aims to comprehensively investigate and analyze the latest applications of human behavior recognition based on channel state information (CSI) and the human skeleton. First, we review the human profile perception and skeleton recognition progress based on wireless perception technologies. Second, we summarize the general framework of precise pose recognition, including signal preprocessing methods, neural network models, and performance results. Then, we classify skeleton model generation methods into three categories and emphasize the crucial difference among these typical applications. Furthermore, we discuss two aspects, such as experimental scenarios and recognition targets. Finally, we conclude the paper by summarizing the issues in typical systems and the main research directions for the future.

Depression and Severity Detection Based on Body Kinematic Features: Using Kinect Recorded Skeleton Data of Simple Action.

Relative limb movement is an important feature in assessing depression. In this study, we looked into whether a skeleton-mimetic task using natural stimuli may help people recognize depression. We innovatively used Kinect V2 to collect participant data. Sequential skeletal data was directly extracted from the original Kinect-3D and tetrad coordinates of the participant's 25 body joints. Two constructed skeletal datasets of whole-body joints (including binary classification and multi classification) were input into the proposed model for depression recognition after data preparation. We improved the temporal convolution network (TCN), creating novel spatial attention dilated TCN (SATCN) network that included a hierarchy of temporal convolution groups with different dilated convolution scales to capture important skeletal features and a spatial attention block for final result prediction. The depression and non-depression groups can be classified automatically with a maximum accuracy of 75.8% in the binary classification task, and 64.3% accuracy in the multi classification dataset to recognize more fine-grained identification of depression severity, according to experimental results. Our experiments and methods based on Kinect V2 can not only identify and screen depression patients but also effectively observe the recovery level of depression patients during the recovery process. For example, in the change from severe depression to moderate or mild depression multi classification dataset.

Human Activity Recognition by Sequences of Skeleton Features.

In recent years, much effort has been devoted to the development of applications capable of detecting different types of human activity. In this field, fall detection is particularly relevant, especially for the elderly. On the one hand, some applications use wearable sensors that are integrated into cell phones, necklaces or smart bracelets to detect sudden movements of the person wearing the device. The main drawback of these types of systems is that these devices must be placed on a person's body. This is a major drawback because they can be uncomfortable, in addition to the fact that these systems cannot be implemented in open spaces and with unfamiliar people. In contrast, other approaches perform activity recognition from video camera images, which have many advantages over the previous ones since the user is not required to wear the sensors. As a result, these applications can be implemented in open spaces and with unknown people. This paper presents a vision-based algorithm for activity recognition. The main contribution of this work is to use human skeleton pose estimation as a feature extraction method for activity detection in video camera images. The use of this method allows the detection of multiple people's activities in the same scene. The algorithm is also capable of classifying multi-frame activities, precisely for those that need more than one frame to be detected. The method is evaluated with the public UP-FALL dataset and compared to similar algorithms using the same dataset.

Atlas of Human Skeleton Hardness Obtained Using the Micro-indentation Technique.

OBJECTIVES: Measure and systematically evaluate the distribution of microhardness in the human skeleton. METHODS: Three fresh corpses were obtained, aged 62 (male), 45 (female), and 58 years (male). Soft tissues were removed, and all axial and unilateral appendicular bones were freshly harvested. All three skeletons were examined by X-ray and computed tomography (CT) to exclude skeletal pathology. Only bones from donors with no known skeletal pathology were included in the study. Axial and unilateral appendicular skeleton bones from each of the three donors were obtained, except for ear ossicles, hyoid bone, tailbone, and 14 phalanges of the foot, for which samples were difficult to obtain. Precision bone specimens with a thickness of 3 mm, which were cut with a Buehler IsoMet 11-1280-250 low-speed diamond saw (Buehler, USA), were obtained from all important anatomic sites in a direction perpendicular to the mechanical axis of each bone. Micro-indentation (the Vickers hardness test) was performed on the surface of each specimen using a microhardness tester with a diamond indenter. Hardness value (HV) was computed for each indentation. Each bone specimen was divided into several regions of interest. Indentations were carefully made and computed. Then we analyzed the data to identify hardness distribution rules at different anatomic sites. RESULTS: In total, 5360 indentations were made in 1072 regions of interest in each donor. Hardness of the axial and appendicular bones were all inhomogeneous depending on the anatomic sites, but the distribution of microhardness followed certain rules. The mean hardness value ranged from 24.46 HV (HV = hardness value, kgf/mm2 ) for the sacrum to 53.20 HV for the shaft of the tibia. The diaphysis was harder than the metaphysis, and the proximal and distal epiphysis had lower values (8.85%- 40.39%) than the diaphysis. Among the long bone diaphyses, the tibia cortical bone (51.20 HV) was the hardest, harder than the humerus (47.25 HV), the ulna (43.26 HV), the radius (42.54 HV), and the femur (47.53 HV). However, in some anatomic sites such as the lumbar vertebra (cortical bone 32.86 HV, cancellous bone 31.25 HV), the cortical shells were sometimes not harder than the internal cancellous bones. The lumbar vertebra (32.86 HV) was harder than the cervical vertebra (28.51 HV) and the thoracic vertebra (29.01 HV). CONCLUSIONS: The distribution of microhardness in the human skeleton follows certain rules. These distribution rules could be used to predict the mechanical properties of bone and progress in this field could provide data for the basis of a new three-dimensional printing technique, which may lead to new perspectives for custom-made implants.

Simple action for depression detection: using kinect-recorded human kinematic skeletal data.

BACKGROUND: Depression, a common worldwide mental disorder, which brings huge challenges to family and social burden around the world is different from fluctuant emotion and psychological pressure in their daily life. Although body signs have been shown to present manifestations of depression in general, few researches focus on whole body kinematic cues with the help of machine learning methods to aid depression recognition. Using the Kinect V2 device to record participants' simple kinematic skeleton data of the participant's body joints, the presented spatial features and low-level features is directly extracted from the record original Kinect-3D coordinates. This research aimed to constructed machine learning model with the preprocessed data importing, which could be used for depression automatic classification. METHODS: Considering some patients' conditions and current status and refer to psychiatrists' advices, simple and significant designed stimulus task will lead human skeleton data collection job. With original Kinect skeleton data extracting and preprocessing, the proposed experiment demonstrated four strong machine learning tools: Support Vector Machine, Logistic Regression, Random Forest and Gradient Boosting. Using the precision, recall, sensitivity, specificity, roc-curve, confusion matrix et.al, indicators were calculated as the measurement of methods, which were commonly used to evaluate classification methodologies. RESULTS: Across screened 64 pairs with age and gender totally matching in depression and control group, and Gradient Boosting achieved the best performance with the prediction accuracy of 76.92%. Sorted by female (54.69%) and male for the gender-based depression recognition, we applied best performance classifier Gradient Boosting got prediction accuracy of 66.67% in the male group, and 71.73% in the female group. Utilizing the best model Gradient Boosting for age-based classification, prediction accuracy got 76.92% in the older group (age >40, 50% of total) and 53.85% accuracy in the younger group (age <= 40). CONCLUSION: The depression and non-depression individuals can be well classified by computational models using Kinect captured skeletal data. The Gradient Boosting, an excellent machine learning tool, get the performance in the four methods we demonstrated. Meanwhile, in the gender-based depression classification also gets reasonable accuracy. In particular, the recognition results of the old group are significantly better than that of the young group. All these findings suggest that kinematic skeletal data based depression recognition can be applied as an effective tool for assisting in depression analysis.

Development of a novel real-time simulation of human skeleton/muscles.

The objective of this research work was to develop a model of human skeleton with the capability of real-time simulation of the physical movements of a person in front of the motion capture hardware (Kinect) in order to analyze the motion data and measure the changes of joint torques. Mevea simulation software has been utilized for this purpose, which is a novel application of this software in the field of biomechanics. The model of the human skeleton was created in Mevea using the graphics built in 3ds Max. Simulink external interface for Mevea was established. Simulink acts as a connection between the Mevea software and Kinect for controlling the model. The developed model has been tested through three case studies involving the elbow joint, thoracic joint, and full body. Changes in torque and angular position of joints based on the input of joints are presented as graphs. The developed real-time model of the human skeleton in Mevea can execute the real-time simulation of a person's movements in front of a motion capture camera and provide the changes of torques, which are dependent on the angular positions of the body joints. This work provides the possibility to use the developed real-time model for physiotherapeutic rehabilitation to identify problematic muscles based on produced torque of the joints in order to specify the therapeutic options. The future research direction would be creating a reference databank by measuring healthy individuals' muscle forces for comparison purposes.

Medical School Hotline: A New Osteological Resource at the John A. Burns School of Medicine.

The Mann-Labrash Osteological Collection of the University of Hawai'i is the newest collection of contemporary known-identity human skeletal remains in the United States. The collection, consisting of the partial or complete remains of individuals of European, African, Asian, and Pacific Islander ancestry, is an invaluable educational and research resource for medical students and visiting researchers. The collection reflects the population diversity of Hawai'i. The Mann-Labrash Osteological Collection provides a unique and irreplaceable resource for medical students and scientists interested in anatomy, disease, trauma, developmental defects, and biological diversity, particularly as they pertain to Hawai'i and the people of Polynesia.

Histomorphometric analysis of the variability of the human skeleton: Forensic implications.

In the last decades, the histomorphometric analysis of bone tissue has been utilized to develop equations for species discrimination of fragmentary bone. Although this technique showed promising results, its main limitation concerns the lack of knowledge on the histomorphometric variability which may exist between different bones of the skeleton. In a previous study, we demonstrated a significant histomorphological variability in different bones of the same individual and even in different sections of the same bone. The present study aimed at investigating the extent of intra-individual variability in bone histomorphometry throughout the human adult skeleton and areas of a single bone. Samples were taken along an entire medieval male adult human skeleton (aged between 26 and 45 years), including long, flat, irregular and sesamoid bones for a total of 49 cross-sections. The histomorphometric analysis revealed that the size of both Haversian systems and Haversian canals were statistically significantly larger in long and irregular bones compared to flat bones. Moreover, osteons were generally bigger in the diaphysis compared to the proximal and distal metaphyses, whereas Haversian canals showed a higher uniformity in the different portions of each bone. The present study has highlighted the importance of conducting similar studies on both human and nonhuman skeletons at different stages of skeletal maturity in order to shed light on the extent of variability in the size of osteons and Haversian canals. This, in fact, represents an important prerequisite to develop reliable histological methods for species discrimination of fragmented bone.

Constraint-Based Optimized Human Skeleton Extraction from Single-Depth Camera.

As a cutting-edge research topic in computer vision and graphics for decades, human skeleton extraction from single-depth camera remains challenging due to possibly occurring occlusions of different body parts, huge appearance variations, and sensor noise. In this paper, we propose to incorporate human skeleton length conservation and symmetry priors as well as temporal constraints to enhance the consistency and continuity for the estimated skeleton of a moving human body. Given an initial estimation of the skeleton joint positions provided per frame by the Kinect SDK or Nuitrack SDK, which do not follow the aforementioned priors and can prone to errors, our framework improves the accuracy of these pose estimates based on the length and symmetry constraints. In addition, our method is device-independent and can be integrated into skeleton extraction SDKs for refinement, allowing the detection of outliers within the initial joint location estimates and predicting new joint location estimates following the temporal observations. The experimental results demonstrate the effectiveness and robustness of our approach in several cases.

Paleopathological Studies of Infectious Disease: Examination of the Osteoarchaeological Research / 체질인류학회지

Reconstructing the impact of infectious disease on past populations is one of the main fields in paleopathological studies. The initial phase of paleopathology was descriptive, focusing on the identification and presence of disease in the past. However, currently paleopathological studies are moving toward probing questions about the larger picture of origin and transmission of disease agents. In this study, paleopathological studies of major infectious disease (i.e., tubuerculosis, treponemal disease and leprosy) were reviewed through osteoarcheological work published in American Journal of Physical Anthropology, International Journal of Osteoarchaeology, Journal of Archaeological Science and International Journal of Paleopathology from 1981 to 2017. A basic objective of this research was to examine many types of research in paleopathology and to characterize research trend in this field. As paleopathological studies becomes more abundant, the approaches to infectious disease have been increasingly specialized and interdisciplinary from 1980. Also, methodology used in paleopathology continues to evolve through the holistic approaches of molecular analysis, radiology and histopathology. Ultimately, this study reinforces the importance for retention of large-scale skeletal collections for paleopathological study in population perspective. In the near future, Korean paleopathology can contribute in the reconstructions of the history of disease and its effect on past human populations.

A large modern Southeast Asian human skeletal collection from Thailand.

The Khon Kaen University Human Skeleton Research Centre has a large human collection consisting of 745 modern northeastern Thai (Isan) skeletons derived from bodies bequeathed to the Department of Anatomy during the period 1979-2014. The aim of this paper is to document the collection and address the question of whether the collection may be representative of local Isan people, or populations of the wider region of mainland Southeast Asia. This will determine its value as a reference collection for forensic anthropology in particular but also for all other fields of research about human skeletal biology. Sex is recorded for 99.6% of the skeletons, and age at death for 91.7%. The collection consists of two-thirds males, one-third females. It includes 10 individuals less than 19 years of age, and adults ranging in age from 20 to 109 years of age. Average age at death is 62 years. Other data available for smaller proportions of the collection include cause of death, occupation, and height and weight at the time of donation. Dates of birth are estimated to range from the late 19th Century to the most recent in 1988. Analysis of the demographic composition of the collection shows that is likely to be representative of the ancestral mix of the Isan people, and of the village farmers who still form a large portion of the Isan population. It may also represent 20th Century populations of much of Southeast Asia where agriculture dominates the economy. The collection forms a valuable resource for research on regional human skeletal characteristics for use in forensic anthropology.

Probable Cases of Scurvy in Subadults Crania from Archaeological Sites, South Korea / 체질인류학회지

In this study, the skeletal abnormalities associated with scurvy in subadults crania from three archaeological skeletal collections (Nukdo, Imdang, Yeanri), South Korea was analyzed to examine the prevalence and distribution of childhood scurvy of ancient Korea. For this, 30 subadults crania from the Nukdo, Imdang, Yeanri site were examined. Using criteria described by Ortner and Ericksen (1997) for identifying scurvy in skeletal material we evaluated the cranial skeleton of the subadults for evidence of abnormal porosity. All skeletal materials were macroscopically evaluated for pathological changes associated with scurvy. In results, lesions indicative of probable scurvy were observed in 22 individuals of 30 individuals. Based on the results, childhood disease relating to nutrition and metabolism in ancient Korea might have been widespread, along with scurvy. The results of the present study will be useful for understanding the health condition of the ancient Korean populations. Future work will add significantly to the larger picture of diet and disease within populations of ancient Korea.

A contemporary Colombian skeletal reference collection: A resource for the development of population specific standards.

Several authors who have discussed human variability and its impact on the forensic identification of bodies pose the need for regional studies documenting the global variation of the attributes analyzed osteological characteristics that aid in establishing biological profile (sex, ancestry, biological age and height). This is primarily accomplished by studying documented human skeletal collections in order to investigate secular trends in skeletal development and aging, among others in the Colombian population. The purpose of this paper is to disclose the details of the new "Contemporary Colombian Skeletal Reference Collection" that currently comprises 600 identified skeletons of both sexes, who died between 2005 and 2008; and which contain information about their cause of death. This collection has infinite potential for research, open to the national and international community, and still has pending opportunities to address a variety of topics such as studies on osteopathology, bone trauma and taphonomic studies.

Potential Use of Bacterial Community Succession in Decaying Human Bone for Estimating Postmortem Interval.

Bacteria are taphonomic agents of human decomposition, potentially useful for estimating postmortem interval (PMI) in late-stage decomposition. Bone samples from 12 individuals and three soil samples were analyzed to assess the effects of decomposition and advancing time on bacterial communities. Results indicated that partially skeletonized remains maintained a presence of bacteria associated with the human gut, whereas bacterial composition of dry skeletal remains maintained a community profile similar to soil communities. Variation in the UniFrac distances was significantly greater between groups than within groups (p < 0.001) for the unweighted metric and not the weighted metric. The members of the bacterial communities were more similar within than between decomposition stages. The oligotrophic environment of bone relative to soft tissue and the physical protection of organic substrates may preclude bacterial blooms during the first years of skeletonization. Therefore, community membership (unweighted) may be better for estimating PMI from skeletonized remains than community structure (weighted).

Automatic measurement of range of motion of human lower limbs using Kinect technique / 中华物理医学与康复杂志

Objective In order to improve the accuracy and efficiency of the measurement of range of motion (ROM) of human lower limbs and simplify process of ROM measurement,an automatic measurement of ROM of human lower limbs based on Kinect technique was proposed and tested in this study.Methods Fifty examinee were randomly divided into 5 groups,namely groups a,b,c,d and e,respectively,each group had 10 members.Using the human skeleton tracking technology from Kinect,the positions of the examinee's lower limbs were captured and tracked by processing the depth data of lower limbs' key joints.Then the information of ROM of hip and knee was output on human-computer interaction interface in real-time.By comparison with traditional manual measurement results,the accuracy of automatic measuring method could be verified.Meanwhile,with the aid of speech recognition and output technology,the mode of warning information transfer and the way of subject switch were optimized.Results According to the method of Grubbs-test and t-test,the ROM values | t | from the subjects' hip abduction (t =0.57,P =0.597),hip adduction (t =0.52,P =0.621),hip anteflexion (t =1.01,P =0.371),hip postextension (t =0.12,P =0.902),hip external rotation (t =0.00,P =1.000),hip internal rotation (t =0.34,P =0.753),knee flexion and extension (t =1.12,P =0.280) all were under the threshold value t0.025 (4) =2.776 on the premise of a level of significance α =0.05,which indicated that there was no significant difference between measured results and expected values(P ＞ 0.05).Conclusion The automatic measurement of ROM of lower limbs can be realized which can improve the measurement accuracy,simplify the measurement process and enhance the practicability of ROM of lower limbs measurement.

An Anthropolgical Study on the Human Skeleton Excavated from Dugmoe Tomb of the Technopols of Kwang Ju City / 체질인류학회지

Authors have anthropologically measured the human skeleton from a Dugmoe Tomb of the technopolis of Kwang-ju city. The results obtained were as follows : 1. The human skeleton was thought to be constructed at the beginning of the period of the Chosun, judging from the Dugmoe Tomb. 2. It is female and its stature is estimated as about 163-165cm. The age of the skeleton is estimated to be late 50. 3. The cranial index is 77.09mm and the type is mesocephaly. 4. The cranial length-height index and the cranial breadth-height index were hypsicrane and acrocephaly. 5. The orbital index 95.0mm and the type is hypsiconch. 6. The humerus is comparatively long, slender and has more rounded diaphysis. 7. The femur is similar that of present day, and the type is platyer. 8. The abrasion of the occlusal surface of the teeth was 2.5 point.