Human Posture Research Articles

Sensor-Based Wearable Systems for Monitoring Human Motion and Posture: A Review.

In recent years, marked progress has been made in wearable technology for human motion and posture recognition in the areas of assisted training, medical health, VR/AR, etc. This paper systematically reviews the status quo of wearable sensing systems for human motion capture and posture recognition from three aspects, which are monitoring indicators, sensors, and system design. In particular, it summarizes the monitoring indicators closely related to human posture changes, such as trunk, joints, and limbs, and analyzes in detail the types, numbers, locations, installation methods, and advantages and disadvantages of sensors in different monitoring systems. Finally, it is concluded that future research in this area will emphasize monitoring accuracy, data security, wearing comfort, and durability. This review provides a reference for the future development of wearable sensing systems for human motion capture.

A computer vision-approach for activity recognition and residential monitoring of elderly people

In this study, we explore a human activity recognition (HAR) system using computer vision for assisted living systems (ALS). Most existing HAR systems are implemented using wired or wireless sensor networks. These systems have limitations such as cost, power issues, weight, and the inability of the elderly to wear and carry them comfortably. These issues could be overcome by a computer vision based HAR system. But such systems require a highly memory-consuming image dataset. Training such a dataset takes a long time. The proposed computer-vision-based system overcomes the shortcomings of existing systems. The authors have used key-joint angles, distances between the key joints, and slopes between the key joints to create a numerical dataset instead of an image dataset. All these parameters in the dataset are recorded via real-time event simulation. The data set has 780,000 calculated feature values from 20,000 images. This dataset is used to train and detect five different human postures. These are sitting, standing, walking, lying, and falling. The implementation encompasses four distinct algorithms: the decision tree (DT), random forest (RF), support vector machine (SVM), and an ensemble approach. Remarkably, the ensemble technique exhibited exceptional performance metrics with 99 ​% accuracy, 98 ​% precision, 97 ​% recall, and an F1 score of 99 ​%.

Human Posture Estimation: A Systematic Review on Force-Based Methods—Analyzing the Differences in Required Expertise and Result Benefits for Their Utilization

Force-based human posture estimation (FPE) provides a valuable alternative when camera-based human motion capturing is impractical. It offers new opportunities for sensor integration in smart products for patient monitoring, ergonomic optimization and sports science. Due to the interdisciplinary research on the topic, an overview of existing methods and the required expertise for their utilization is lacking. This paper presents a systematic review by the PRISMA 2020 review process. In total, 82 studies are selected (59 machine learning (ML)-based and 23 digital human model (DHM)-based posture estimation methods). The ML-based methods use input data from hardware sensors—mostly pressure mapping sensors—and trained ML models for estimating human posture. The ML-based human posture estimation algorithms mostly reach an accuracy above 90%. DHMs, which represent the structure and kinematics of the human body, adjust posture to minimize physical stress. The required expert knowledge for the utilization of these methods and their resulting benefits are analyzed and discussed. DHM-based methods have shown their general applicability without the need for application-specific training but require expertise in human physiology. ML-based methods can be used with less domain-specific expertise, but an application-specific training of these models is necessary.

Azure Kinect performance evaluation for human motion and upper limb biomechanical analysis

Human motion tracking is a valuable task for many medical applications. Marker-based optoelectronic systems are considered the gold standard in human motion tracking. However, their use is not always feasible in clinics and industrial environments. On the other hand, marker-less sensors became valuable tools, as they are inexpensive, noninvasive and easy to use. However, their accuracy can depend on many factors including sensor positioning, light conditions and body occlusions. In this study, following previous works on the feasibility of marker-less systems for human motion monitoring, we investigate the performance of the Microsoft Azure Kinect sensor in computing kinematic and dynamic measurements of static postures and dynamic movements. According to our knowledge, it is the first time that this sensor is compared with a Vicon marker-based system to assess the best camera positioning while observing the upper body part movements of people performing several tasks. Twenty-five healthy volunteers were monitored to evaluate the effects of the several testing conditions, including the Azure Kinect positions, the light conditions, and lower limbs occlusions, on the tracking accuracy of kinematic, dynamic, and motor control parameters. From the statistical analysis of the performed measurements, the camera in the frontal position was the most reliable, the lighting conditions had almost no effects on the tracking accuracy, while the lower limbs occlusion worsened the accuracy of the upper limbs. The assessment of human static postures and dynamic movements based on experimental data proves the feasibility of applying the Azure Kinect to the biomechanical monitoring of human motion in several fields.

Motor units involvement in diaphragm and intercostal muscles during supine and prone posture, and its relationship with oxygen saturation and perfusion index in healthy young female adults

Objectives: Due to gravity and non-gravity variables, human posture influences the distribution of ventilation and perfusion. Gravity enhances the air exchange and posture has an impact on the respiratory muscles’ activity. The goal of the study was to determine the role of neuromuscular activities in respiratory muscles throughout various respiratory states and postures, as well as the degree to which two different lying positions affected the perfusion index (PI) and oxygen saturation (SpO2) level in young, healthy female adults. Materials and Methods: Thirty sedentary healthy female college students, age ranges from 18 to 25 years having no history of pulmonary or neuromuscular diseases voluntarily cooperated and participated in this study. Each participant’s diaphragm and intercostal muscles underwent surface electromyography in the supine and prone postures. The heart rate (HR), SpO2, and PI were measured. Results: When in the supine position, the diaphragm and intercostal muscles both had greater mean root mean square and maximum voluntary contraction values, which is statistically significant (P < 0.05). However, HR, SpO2 level, and PI between supine and prone postures show negligible changes. Conclusion: According to this study, prone posture is advantageous to supine posture since it requires less motor unit activation for proper breathing. Contrarily, the increases in chest cavity capacity are insufficient for the healthy adult female’s calm breathing to result in an increase in SpO2 and PI.

Research on the Analysis of Traditional Dance Performance Forms and Dance Movement Characteristics Based on Artificial Intelligence Technology

Abstract This paper analyzes the performance forms and movement characteristics of traditional dances by using the method of movement feature extraction. We construct a dance key movement extraction system by merging optical flow computing and extracting the key movements of music and dance, which increases the efficiency of traditional dance movement analysis and reduces computational complexity. We can improve the similarity matching of human posture when using picture entropy computation. It uses an optical capture technique to record lively dancing motions. The results show that the accuracy of optical flow computation is 0.8 for distinguishing the form of the cultural lion performance, 0.85 for distinguishing the martial lion performance, 0.75 for distinguishing the aerial lion performance, and 0.6 for capturing the tumbling movement of the cultural lion and 0.7 for capturing the frolicking movement under the optical motion capture system.

Panorama historique de l’étude de la réfraction astronomique : une histoire méconnue entre optique, mathématiques et géodésie

From Greek antiquity to the era of computer science, astronomical refraction has raised questions about the real angular position of celestial bodies as seen from Earth surface, the structure of its atmosphere, and the celestial navigation. After introducing the embryonic ideas and the first measurements, the article first presents the early founders of a mathematically structured study: Cassini, Newton, Taylor—the last two inventing appropriate mathematical tools. Then the 18th century geodesists (Bouguer, Lacaille, etc.) enrich the corpus of observations to be understood, followed by the “classics”—Simpson, Bradley, Kramp, Laplace. The progress in metrology allows precise studies of the air refractive index and new theoretical efforts with Biot’s omnipresence. This gain in accuracy requires new calculations involving more sophisticated atmospheric models, as Radau and Ivory, among others, will do. Ivory pointing out a divergence in the numerical series being used, Kummer and Hausdorff find a new mathematical way. Numerical work on computers is eventually making useless all this mathematical virtuosity, although present work keeps relying on Biot’s theoretical advances.

Modeling Planetary and Stellar Motion Using Differential Equations

The report aims to explore the application of differential equations in modeling the motion of planets and stars within our universe, serving as an introduction to the captivating realm of celestial mechanics. We utilize differential equations to represent the movement and positions of celestial bodies within a gravitational field, grounding our analysis in Newton's laws of motion and gravitation. Moreover, we employ Kepler's laws of planetary motion to elucidate the orbits of planets around the sun. It is important to note that this report offers a simplified perspective, designed for educational purposes. In reality, celestial mechanics can be exceedingly intricate, involving n-body problems, relativistic effects, and a multitude of other factors.

Collecting the energy generated by manual workers to monitor their working status and improve their working conditions by using a flexible rack mechanism

Currently, an increasing quantity of portable energy harvesting modules are being developed to capture the energy generated by human motion. However, the size and weight of a device can affect the smoothness and comfort of a user’s normal limb movements in the process of collecting energy generated by human movement. Especially on manual workers, this effect will significantly increase their physical exertion, so the design of energy-harvesting devices for wearing on manual workers has higher requirements. The bend knee energy harvester (BKEH) designed in the work presented in this paper used a laboratory-made flexible rack to harvest the energy generated by manual workers’ frequently bent knees during work. It converts the collected energy into electricity for various wearable devices to monitor the working status of manual workers and improve their working conditions. One end of the flexible rack is fixed to the upper thigh. When the user bends the knee, the flexible rack will move downward, causing the gear to rotate, thereby collecting the energy generated by the body’s movement. The BKEH was made of many lightweight materials and weighed only 406 g, greatly reducing the impact on the user’s normal limb movements and physical exertion. Practical experiments showed that the BKEH output open-circuit voltage is up to 80.3 V, the output power reached as high as 3.16 W, and the power density reached as high as 7.9 W kg−1, which can effectively supply sufficient electrical power for wearable devices to work normally. The BKEH has a high practical value and good adaptability to human movement posture and can generate enough voltage and power to allow some wearable devices to work properly. These wearable devices can effectively provide users with the ability to monitor their work status and improve working conditions.

Product Design-based on an Auxiliary System of Fatigue Driving

Starting from the effects and hazards of fatigue driving, this paper analyzes the current mainstream fatigue driving monitoring scheme: determining whether a driver is in a fatigued driving state by detecting his or her facial features. The idea of aiding this scheme through physical methods is proposed, and a preliminary feasibility discussion and design are presented. The main design solution is to provide a real-time and continuous aid to the facial monitoring method by monitoring the human posture in real time with thin-film sensors, which are installed on the inner side of the steering wheel and under the seat and backrest. Whether this installation would cause discomfort to the driver and how to alert the driver were also considered. Finally, based on the existing design, the possibility of improving the solution is proposed and how it should be implemented afterwards.

Толкование правовых категорий «презумпция невиновности» и «разумный срок судебного разбирательства» в практике межгосударственных органов по правам человека (сравнительный анализ)

The presumption of innocence and a reasonable time of trial are the fundamental guarantees of a person who is a participant in criminal proceedings. The comparative legal analysis examines the legal positions of intergovernmental human rights bodies regarding such elements of the right to a fair trial as the «presumption of innocence» and the «reasonable time of trial».

Концептуальные основы влияния практики межгосударственных органов по правам человека в национальное законодательство государств

The article examines some theoretical aspects of the influence of the practice of interstate human rights bodies on the national legislation of states. The article analyzes the conditions under which it is possible to implement the positions of interstate human rights bodies in national legislation. And the conditions under which this practice does not conflict with the sovereign rights of the state.

Numerical Modeling and Simulation of Fractured-Vuggy Reservoirs Based on Field Outcrops

We propose a novel workflow to investigate the complex flow behaviors and remaining oil distribution related to the oil–gas–water three-phase system based on information from typical outcrops of fractured-vuggy reservoirs. A refined geological model is built to represent the size, geometry, and spatial distribution of the karst caves and fractures extracted from the field outcrop photographs. The combination of the perpendicular bisector (PEBI) grid technique and the control-volume finite difference method is adopted for space discretization. We have validated the numerical model against experimental data. Numerical simulations were performed to explore the impacts of the permeability of karst cave and natural fractures and the position of natural water bodies upon oil production performance. Numerical results indicate that (1) the cave permeability has few impacts on the oil production, yet the fracture permeability plays a significant role in determining the oil recovery; (2) a higher permeability of the fractures will lead to a longer period of time for no-water oil production and, thus, a higher oil recovery; (3) the position of natural water body shows significant impacts on oil recovery, e.g., a short distance between the natural water body and the production well tends to form preferential passages, causing severe reduction of water flooding range; and (4) the distribution of remaining oil is controlled by spatial patterns of the fractured-vuggy system and reservoir development schemes. We found that the remaining oil is mainly distributed along the model boundaries and at the corner of the caves with single or multiple connection/s to fractures.

Non-invasive human thermal comfort assessment based on multiple angle/distance facial key-region temperatures recognition

Accurate monitoring of human thermal comfort is crucial in optimizing HVAC system control scheme and enhancing building energy efficiency. The method based on facial temperature infrared recognition is a non-invasive and real-time thermal comfort predictive strategy, which has been proven great application potential. In response to the limitations of previous fixed-position facial infrared detection in practical applications, this study aims to explore a less restrictive non-intrusive method for assessing human thermal comfort. The temperature features of multiple regions on human face are identified by an infrared camera, and six temperature-sensitive regions are selected through skin thermal sensitivity analysis. Thirty subjects participate in a series of field experiments. To reduce the measurement limitations caused by human postures, the correlation between these six facial regions, indoor air temperature, thermal sensation votes (TSV), and thermal comfort votes (TCV) are analyzed in details to determine two key facial regions for the non-intrusive thermal comfort assessment. By applying the YOLOv5 algorithm, the real-time extraction of facial region temperatures from multiple angles and distances is achieved. On this basis, a data-driven thermal comfort predictive strategy based on facial temperature and optimized SVM model is designed. Results indicate that the method achieves a general accuracy of 85.68% in predicting thermal comfort based on its successful recognition rate of 88.7% for facial key regions.

The Three-Dimensional Body Center of Mass at the Workplace under Hypogravity.

The center of mass dynamics of the seated posture of humans in a work environment under hypogravity (0 < g < 1) have rarely been investigated, and such research is yet to be carried out. The present study determined the difference in the body system of 32 participants working under simulated 1/6 g (Moon) and 1 g (Earth) for comparison using static and dynamic task measurements. This was based on a markerless motion capture method that analyzed participants' center of mass at the start, middle and end of the task when they began to get fatigued. According to this analysis, there is a positive relationship (p < 0.01) with a positive coefficient of correlation between the downward center of mass body shift along the proximodistal axis and gravity level for males and females. At the same time, the same positive relationship (p < 0.01) between the tilt of the body backward along the anterior-posterior axis and the level of gravity was found only in females. This offers fresh perspectives for comprehending hypogravity in a broader framework regarding its impact on musculoskeletal disorders. It can also improve workplace ergonomics, body stability, equipment design, and biomechanics.

SKT-MOT and DyTracker: A Multiobject Tracking Dataset and a Dynamic Tracker for Speed Skating Video

Speed skating serves as a significant application domain for multiobject tracking (MOT), presenting unique challenges such as frequent occlusion, highly similar appearances, and motion blur. To address these challenges, this paper constructs an MOT dataset called SKT-MOT for speed skating and analyzes the shortcomings of existing datasets and methods. Accordingly, we propose a dynamic MOT method called DyTracker. The method builds upon the DeepSORT baseline and enhances three key modules. At the global level, we design the track dynamic management (TDM) algorithm. In the motion branch, a novel metric is proposed to evaluate occlusion and Kalman filter dynamic update (KFDU) is implemented. In the appearance branch, we account for the difference in human posture and propose the feature dynamic selection and updating (FDSU) strategy. This makes our DyTracker flexible and efficient to achieve a multiobject tracking accuracy (MOTA) of 93.70% and identification F1 (IDF1) score of 92.39% on SKT-MOT, which is a significant advantage over existing SOTA methods. To validate the generalization of our proposed module, two dynamic update modules are inserted into other methods and validated on the public dataset MOT17, and the accuracy is generally improved by 0.2%–0.6%.

The triboelectric sensor based on PDMS/SGO for human running posture and physical fitness health monitoring

ABSTRACT Recently, research about the intelligent sports equipment based on triboelectric sensor for athlete posture monitoring has made progress. However, the exploration of new triboelectric materials remains an important challenge to be faced. Hence, we ingeniously design a polydimethylsiloxane (PDMS)/silanized graphite oxide (SGO)-based triboelectric nanogenerator (PS-TENG) for running posture and physical health monitoring. The introduction of SGO has improved the electron capture capability of PDMS, thereby achieving high output of PS-TENG. From the results, under an 60 MΩ resistance, the power density of PS-TENG reaches a peak of 1780 mW·m−2. Furthermore, athletes undergo various postures during the running process, so monitoring special postures is very meaningful, such as jogging, long jump, walking, etc. Especially, according to the self-charging mechanism, PS-TENG can indirectly evaluate physical energy analysis during running by storing electrical energy in capacitors. This triboelectric sensor can assist in posture monitoring and physical fitness monitoring during running.

Musicianship and the masteries of the stars: music and musicians in the Liber Nativitatum

AbstractThis article shines a light on the musical contents of a “book of births”, the Liber Nativitatum or Albubather, written by the Persian Astrologer Abu Bakr al‐Hassan ibn al‐Khasib in the ninth century, translated into Latin at the beginning of the thirteenth century, and published in Venice in 1501. “Books of births” served to show how an individual's fortune and personal traits could be ascertained from the position of the celestial bodies throughout the individual's gestation period. A significant portion of these traits pertain to loquacity, hearing, musical skill and the likelihood of a musical profession. Thanks to the connotations each celestial body bore – positive and negative – and the traits they are described as imparting, the Liber Nativitatum makes it possible to identify the skills and traits requisite for good musical performance, as well as those traits which might inhibit it.

A Smart, Textile-Driven, Soft Exosuit for Spinal Assistance.

Work-related musculoskeletal disorders (WMSDs) are often caused by repetitive lifting, making them a significant concern in occupational health. Although wearable assist devices have become the norm for mitigating the risk of back pain, most spinal assist devices still possess a partially rigid structure that impacts the user's comfort and flexibility. This paper addresses this issue by presenting a smart textile-actuated spine assistance robotic exosuit (SARE), which can conform to the back seamlessly without impeding the user's movement and is incredibly lightweight. To detect strain on the spine and to control the smart textile automatically, a soft knitting sensor that utilizes fluid pressure as a sensing element is used. Based on the soft knitting hydraulic sensor, the robotic exosuit can also feature the ability of monitoring and rectifying human posture. The SARE is validated experimentally with human subjects (N = 4). Through wearing the SARE in stoop lifting, the peak electromyography (EMG) signals of the lumbar erector spinae are reduced by 22.8% ± 12 for lifting 5 kg weights and 27.1% ± 14 in empty-handed conditions. Moreover, the integrated EMG decreased by 34.7% ± 11.8 for lifting 5 kg weights and 36% ± 13.3 in empty-handed conditions. In summary, the artificial muscle wearable device represents an anatomical solution to reduce the risk of muscle strain, metabolic energy cost and back pain associated with repetitive lifting tasks.

Design of dynamic ski motion capture and human posture detection model based on spatio-temporal Transformer and wireless device tracking technology.

As a result of significant advancements in living conditions, individuals have redirected their attention towards physical exercise. Skiing, as a widely popular sport, necessitates the real-time maintenance of correct posture during movement. Therefore, we present a dynamic skiing motion capture and human posture detection model that leverages wireless device tracking. Primarily, personnel tracking is enabled through the construction of service base stations and the utilization of wireless device tracking technology. Subsequently, a human posture detection model is formulated in the form of human posture key points, employing the image information of each frame obtained via wireless devices. Finally, we introduce a spatio-temporal Transformer structure that facilitates the detection and recognition of human posture in consecutive frames. Our results demonstrate that our approach can precisely locate and track the position of skiing personnel. Compared to the latest Blip and Conformer methods, our technique yields F values that surpass them by 1.20% and 4.51%, respectively. Moreover, our model can achieve convergent model parameters and accomplish training objectives more efficiently, thus enabling posture detection and dynamic capture of skiing personnel via image and video information.