scholarly journals Accelerometry-Based Distance Estimation for Ambulatory Human Motion Analysis

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4441 ◽  
Author(s):  
Juan Alvarez ◽  
Diego Álvarez ◽  
Antonio López
Keyword(s):  
Human Motion ◽  
Position Estimation ◽  
The Body ◽  
Sensor Data ◽  
Experimental Comparison ◽  
Integration Time ◽  
Human Motion Analysis ◽  
Body Parts ◽  
Mean Velocity ◽  
Wide Range

In human motion science, accelerometers are used as linear distance sensors by attaching them to moving body parts, with their measurement axes its measurement axis aligned in the direction of motion. When double integrating the raw sensor data, multiple error sources are also integrated integrated as well, producing inaccuracies in the final position estimation which increases fast with the integration time. In this paper, we make a systematic and experimental comparison of different methods for position estimation, with different sensors and in different motion conditions. The objective is to correlate practical factors that appear in real applications, such as motion mean velocity, path length, calibration method, or accelerometer noise level, with the quality of the estimation. The results confirm that it is possible to use accelerometers to estimate short linear displacements of the body with a typical error of around 4.5% in the general conditions tested in this study. However, they also show that the motion kinematic conditions can be a key factor in the performance of this estimation, as the dynamic response of the accelerometer can affect the final results. The study lays out the basis for a better design of distance estimations, which are useful in a wide range of ambulatory human motion monitoring applications.

scholarly journals Custom IMU-Based Wearable System for Robust 2.4 GHz Wireless Human Body Parts Orientation Tracking and 3D Movement Visualization on an Avatar

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6642
Author(s):  
Javier González-Alonso ◽  
David Oviedo-Pastor ◽  
Héctor J. Aguado ◽  
Francisco J. Díaz-Pernas ◽  
David González-Ortega ◽  
...  
Keyword(s):  
Real Time ◽  
Motion Analysis ◽  
Human Body ◽  
Human Motion ◽  
Measurement Unit ◽  
Human Motion Analysis ◽  
Body Parts ◽  
Entry Level ◽  
Wide Range ◽  
Do It Yourself

Recent studies confirm the applicability of Inertial Measurement Unit (IMU)-based systems for human motion analysis. Notwithstanding, high-end IMU-based commercial solutions are yet too expensive and complex to democratize their use among a wide range of potential users. Less featured entry-level commercial solutions are being introduced in the market, trying to fill this gap, but still present some limitations that need to be overcome. At the same time, there is a growing number of scientific papers using not commercial, but custom do-it-yourself IMU-based systems in medical and sports applications. Even though these solutions can help to popularize the use of this technology, they have more limited features and the description on how to design and build them from scratch is yet too scarce in the literature. The aim of this work is two-fold: (1) Proving the feasibility of building an affordable custom solution aimed at simultaneous multiple body parts orientation tracking; while providing a detailed bottom-up description of the required hardware, tools, and mathematical operations to estimate and represent 3D movement in real-time. (2) Showing how the introduction of a custom 2.4 GHz communication protocol including a channel hopping strategy can address some of the current communication limitations of entry-level commercial solutions. The proposed system can be used for wireless real-time human body parts orientation tracking with up to 10 custom sensors, at least at 50 Hz. In addition, it provides a more reliable motion data acquisition in Bluetooth and Wi-Fi crowded environments, where the use of entry-level commercial solutions might be unfeasible. This system can be used as a groundwork for developing affordable human motion analysis solutions that do not require an accurate kinematic analysis.

scholarly journals Characterisation of human gait using a continuous-wave radar at 24 GHz

2008 ◽  
Vol 6 ◽  
pp. 67-70 ◽  
Author(s):  
C. Hornsteiner ◽  
J. Detlefsen
Keyword(s):  
Moving Objects ◽  
Continuous Wave ◽  
The Body ◽  
Human Gait ◽  
Radar Signal ◽  
Body Parts ◽  
Mean Velocity ◽  
Time Frequency ◽  
Wave Radar ◽  
Wide Range

Abstract. Human locomotion consists of a complex movement of various parts of the body. The reflections generated by body parts with different relative velocities result in different Doppler shifts which can be detected as a superposition with a Continuous-Wave (CW) Radar. A time-frequency transform like the short-time Fourier transform (STFT) of the radar signal allows a representation of the signal in both time- and frequency domain (spectrogram). It can be shown that even during one gait cycle the velocity of the torso, which constitutes the major part of the reflection, is not constant. Further a smaller portion of the signal is reflected from the legs. The velocity of the legs varies in a wide range from zero (foot is on the ground) to a velocity which is higher than that of the torso. The two dominant parameters which characterise the human gait are the step rate and the mean velocity. Both parameters can be deduced from suitable portions of the spectrogram. The statistical evaluation of the two parameters has the potential to be included for discrimination purposes either between different persons or between humans and other moving objects.

scholarly journals EXPERIMENTAL COMPARISON BETWEEN MAHONEY AND COMPLEMENTARY SENSOR FUSION ALGORITHM FOR ATTITUDE DETERMINATION BY RAW SENSOR DATA OF XSENS IMU ON BUOY

2017 ◽  
Vol XLII-4/W4 ◽  
pp. 497-502 ◽  
Author(s):  
A. Jouybari ◽  
A. A. Ardalan ◽  
M.-H. Rezvani
Keyword(s):  
Critical Role ◽  
Euler Angle ◽  
Human Motion ◽  
Sensor Data ◽  
Experimental Comparison ◽  
Human Motion Analysis ◽  
Euler Angles ◽  
Fusion Algorithm ◽  
Raw Data ◽  
Complementary Filter

The accurate measurement of platform orientation plays a critical role in a range of applications including marine, aerospace, robotics, navigation, human motion analysis, and machine interaction. We used Mahoney filter, Complementary filter and Xsens Kalman filter for achieving Euler angle of a dynamic platform by integration of gyroscope, accelerometer, and magnetometer measurements. The field test has been performed in Kish Island using an IMU sensor (Xsens MTi-G-700) that installed onboard a buoy so as to provide raw data of gyroscopes, accelerometers, magnetometer measurements about 25 minutes. These raw data were used to calculate the Euler angles by Mahoney filter and Complementary filter, while the Euler angles collected by XSense IMU sensor become the reference of the Euler angle estimations. We then compared Euler angles which calculated by Mahoney Filter and Complementary Filter with reference to the Euler angles recorded by the XSense IMU sensor. The standard deviations of the differences between the Mahoney Filter, Complementary Filter Euler angles and XSense IMU sensor Euler angles were about 0.5644, 0.3872, 0.4990 degrees and 0.6349, 0.2621, 2.3778 degrees for roll, pitch, and heading, respectively, so the numerical result assert that Mahoney filter is precise for roll and heading angles determination and Complementary filter is precise only for pitch determination, it should be noted that heading angle determination by Complementary filter has more error than Mahoney filter.

scholarly journals Optical Wireless Network Design for Off-Body-Sensor Based Monitoring

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
T. B. Hoang ◽  
S. Sahuguede ◽  
A. Julien-Vergonjanne
Keyword(s):  
Health Monitoring ◽  
Visible Light Communication ◽  
The Body ◽  
Sensor Data ◽  
Body Parts ◽  
Optical Technology ◽  
Wireless Network Design ◽  
Response Sets ◽  
Trade Offs ◽  
The Impact

In this article, we propose an all-optical bidirectional wireless communication system for off-body sensor communication. Optical technology uses infrared (IR) for uplinks and visible light communication (VLC) for downlinks. From numerical simulations, we discuss the impact of body sensor positions on IR and VLC channels. Our goal is to evaluate the possibilities of using optical technology to transmit sensor data for extreme positions such as the ankle, for which the presence of the body creates blockages. In addition, we also consider the variations in orientation of transceivers due to random mobility of body parts during normal movement. Based on a statistical approach, we evaluate performance in terms of outage probability using channel impulse response sets corresponding to the studied scenario, which is health monitoring. Considering a given quality of service, we address trade-offs related to emitting power and data rate. We discuss the results regarding sensor node position and body reflectivity specifically for ankle sensors, corresponding to an extreme but realistic position in the health-monitoring context.

scholarly journals SteadEye-Head—Improving MARG-Sensor Based Head Orientation Measurements Through Eye Tracking Data

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2759 ◽  
Author(s):  
Lukas Wöhle ◽  
Marion Gebhard
Keyword(s):  
Data Fusion ◽  
Eye Tracking ◽  
Medical Diagnostics ◽  
Human Motion ◽  
Rehabilitation Robotics ◽  
Sensor Data ◽  
Head Orientation ◽  
Human Motion Analysis ◽  
Tracking Data ◽  
Sensor Data Fusion

This paper presents the use of eye tracking data in Magnetic AngularRate Gravity (MARG)-sensor based head orientation estimation. The approach presented here can be deployed in any motion measurement that includes MARG and eye tracking sensors (e.g., rehabilitation robotics or medical diagnostics). The challenge in these mostly indoor applications is the presence of magnetic field disturbances at the location of the MARG-sensor. In this work, eye tracking data (visual fixations) are used to enable zero orientation change updates in the MARG-sensor data fusion chain. The approach is based on a MARG-sensor data fusion filter, an online visual fixation detection algorithm as well as a dynamic angular rate threshold estimation for low latency and adaptive head motion noise parameterization. In this work we use an adaptation of Madgwicks gradient descent filter for MARG-sensor data fusion, but the approach could be used with any other data fusion process. The presented approach does not rely on additional stationary or local environmental references and is therefore self-contained. The proposed system is benchmarked against a Qualisys motion capture system, a gold standard in human motion analysis, showing improved heading accuracy for the MARG-sensor data fusion up to a factor of 0.5 while magnetic disturbance is present.

scholarly journals Human Motion Gesture Recognition Based on Computer Vision

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Rui Ma ◽  
Zhendong Zhang ◽  
Enqing Chen
Keyword(s):  
Computer Vision ◽  
Gesture Recognition ◽  
Human Body ◽  
Spatial Relationship ◽  
Research Direction ◽  
Human Motion ◽  
The Body ◽  
Body Parts ◽  
Human Body Model ◽  
Relationship Of

Human motion gesture recognition is the most challenging research direction in the field of computer vision, and it is widely used in human-computer interaction, intelligent monitoring, virtual reality, human behaviour analysis, and other fields. This paper proposes a new type of deep convolutional generation confrontation network to recognize human motion pose. This method uses a deep convolutional stacked hourglass network to accurately extract the location of key joint points on the image. The generation and identification part of the network is designed to encode the first hierarchy (parent) and the second hierarchy (child) and show the spatial relationship of human body parts. The generator and the discriminator are designed as two parts in the network, and they are connected together in order to encode the possible relationship of appearance and, at the same time, the possibility of the existence of human body parts and the relationship between each part of the body and its parental part coding. In the image, the key nodes of the human body model and the general body posture can be identified more accurately. The method has been tested on different data sets. In most cases, the results obtained by the proposed method are better than those of other comparison methods.

Reorganization in the Cutaneous Core of the Human Thalamic Principal Somatic Sensory Nucleus (Ventral Caudal) in Patients With Dystonia

1999 ◽  
Vol 82 (6) ◽  
pp. 3204-3212 ◽  
Author(s):  
Fred A. Lenz ◽  
Nancy N. Byl
Keyword(s):  
Essential Tremor ◽  
Average Length ◽  
Receptive Fields ◽  
Body Part ◽  
The Body ◽  
Sensory Cortex ◽  
Body Parts ◽  
Primary Sensory Cortex ◽  
Wide Range ◽  
Sensory Nucleus

A wide range of observations suggest that sensory inputs play a significant role in dystonia. For example, the map of the hand representation in the primary sensory cortex (area 3b) is altered in monkeys with dystonia-like movements resulting from overtraining in a gripping task. We investigated whether similar reorganization occurs in the somatic sensory thalamus of patients with dystonia (dystonia patients). We studied recordings of neuronal activity and microstimulation-evoked responses from the cutaneous core of the human principal somatic sensory nucleus (ventral caudal, Vc) of 11 dystonia patients who underwent stereotactic thalamotomy. Fifteen patients with essential tremor who underwent similar procedures were used as controls. The cutaneous core of Vc was defined as the part of the cellular thalamic region where the majority of cells had receptive fields (RFs) to innocuous cutaneous stimuli. The proportion of RFs including multiple parts of the body was greater in dystonia patients (29%) than in patients with essential tremor (11%). Similarly, the percentage of projected fields (PFs) including multiple body parts was higher in dystonia patients (71%) than in patients with essential tremor (41%). A match at a thalamic site was said to occur if the RF and PF at that site included a body part in common. Such matches were significantly less prevalent in dystonia patients (33%) than in patients with essential tremor (58%). The average length of the trajectory where the PF included a consistent, cutaneous RF was significantly longer in patients with dystonia than in control patients with essential tremor. The findings of sensory reorganization in Vc thalamus are congruent with those reported in the somatic sensory cortex of monkeys with dystonia-like movements resulting from overtraining in a gripping task.

Human Motion Capture with Sparse Inertial Sensors and Video

2020 ◽  
Author(s):  
Timo von Marcard
Keyword(s):  
Global Optimization ◽  
Optimization Problem ◽  
Inertial Sensors ◽  
Inertial Sensor ◽  
Hybrid Approach ◽  
Human Motion ◽  
The Body ◽  
Sensor Data ◽  
Discrete Optimization Problem ◽  
Global Optimization Problem

This thesis explores approaches to capture human motions with a small number of sensors. In the first part of this thesis an approach is presented that reconstructs the body pose from only six inertial sensors. Instead of relying on pre-recorded motion databases, a global optimization problem is solved to maximize the consistency of measurements and model over an entire recording sequence. The second part of this thesis deals with a hybrid approach to fuse visual information from a single hand-held camera with inertial sensor data. First, a discrete optimization problem is solved to automatically associate people detections in the video with inertial sensor data. Then, a global optimization problem is formulated to combine visual and inertial information. The propose  approach enables capturing of multiple interacting people and works even if many more people are visible in the camera image. In addition, systematic inertial sensor errors can be compensated, leading to a substantial in...

LOG-TRACKER: AN ATTRIBUTE-BASED APPROACH TO TRACKING HUMAN BODY MOTION

1991 ◽  
Vol 05 (03) ◽  
pp. 439-458 ◽  
Author(s):  
WARREN LONG ◽  
YEE-HONG YANG
Keyword(s):  
Human Body ◽  
Moving Objects ◽  
Human Motion ◽  
The Body ◽  
Body Motion ◽  
Body Parts ◽  
Short Period ◽  
Recognition Of Objects ◽  
Analysis System ◽  
Key Steps

Motion provides extra information that can aid in the recognition of objects. One of the most commonly seen objects is, perhaps, the human body. Yet little attention has been paid to the analysis of human motion. One of the key steps required for a successful motion analysis system is the ability to track moving objects. In this paper, we describe a new system called Log-Tracker, which was recently developed for tracking the motion of the different parts of the human body. Occlusion of body parts is termed a forking condition. Two classes of forks as well as the attributes required to classify them are described. Experimental results from two gymnastics sequences indicate that the system is able to track the body parts even when they are occluded for a short period of time. Occlusions that extend for a long period of time still pose problems to Log-Tracker.

Real-Time Motion Capture for a Human Body using Accelerometers

Robotica ◽  
2001 ◽  
Vol 19 (6) ◽  
pp. 601-610 ◽  
Author(s):  
Jihong Lee ◽  
Insoo Ha
Keyword(s):  
Real Time ◽  
Motion Capture ◽  
Human Body ◽  
Degrees Of Freedom ◽  
Low Cost ◽  
Human Motion ◽  
The Body ◽  
Sensor Data ◽  
Time Motion ◽  
Gravity Acceleration

In this paper we propose a set of techniques for a real-time motion capture of a human body. The proposed motion capture system is based on low cost accelerometers, and is capable of identifying the body configuration by extracting gravity-related terms from the sensor data. One sensor unit is composed of 3 accelerometers arranged orthogonally to each other, and is capable of identifying 2 rotating angles of joints with 2 degrees of freedom. A geometric fusion technique is applied to cope with the uncertainty of sensor data. A practical calibration technique is also proposed to handle errors in aligning the sensing axis to the coordination axis. In the case where motion acceleration is not negligible compared with gravity acceleration, a compensation technique to extract gravity acceleration from the sensor data is proposed. Experimental results not only for individual techniques but also for human motion capturing with graphics are included.

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