Application research of wearable sensors and actuators in biomechanics of lower limbs

2021 ◽  
Author(s):  
Qinyuan Yu ◽  
Bin Wang ◽  
Rongzhou Zhong ◽  
Yanjun Jin ◽  
Zhe Li ◽  
...  
Keyword(s):  
Wearable Sensors ◽  
Lower Limbs ◽  
Application Research ◽  
Sensors And Actuators

scholarly journals Analysis of 3-D Kinematics Using H-Gait System during Walking on a Lower Body Positive Pressure Treadmill

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2619
Author(s):  
Yoshiaki Kataoka ◽  
Ryo Takeda ◽  
Shigeru Tadano ◽  
Tomoya Ishida ◽  
Yuki Saito ◽  
...  
Keyword(s):  
Motion Analysis ◽  
Wearable Sensors ◽  
Three Dimensional ◽  
Lower Limbs ◽  
Positive Pressure ◽  
Lower Body ◽  
Lower Body Positive Pressure ◽  
Gait Kinematics ◽  
Peak Knee ◽  
Body Positive

Recently, treadmills equipped with a lower-body positive-pressure (LBPP) device have been developed to provide precise body weight support (BWS) during walking. Since lower limbs are covered in a waist-high chamber of an LBPP treadmill, a conventional motion analysis using an optical method is impossible to evaluate gait kinematics on LBPP. We have developed a wearable-sensor-based three-dimensional motion analysis system, H-Gait. The purpose of the present study was to investigate the effects of BWS by a LBPP treadmill on gait kinematics using an H-Gait system. Twenty-five healthy subjects walked at 2.5 km/h on a LBPP treadmill under the following three conditions: (1) 0%BWS, (2) 25%BWS and (3) 50%BWS conditions. Acceleration and angular velocity from seven wearable sensors were used to analyze lower limb kinematics during walking. BWS significantly decreased peak angles of hip adduction, knee adduction and ankle dorsiflexion. In particular, the peak knee adduction angle at the 50%BWS significantly decreased compared to at the 25%BWS (p = 0.012) or 0%BWS (p < 0.001). The present study showed that H-Gait system can detect the changes in gait kinematics in response to BWS by a LBPP treadmill and provided a useful clinical application of the H-Gait system to walking exercises.

scholarly journals High-Level Features for Recognizing Human Actions in Daily Living Environments Using Wearable Sensors

Proceedings ◽  
2018 ◽  
Vol 2 (19) ◽  
pp. 1238 ◽  
Author(s):  
Irvin López-Nava ◽  
Angélica Muñoz-Meléndez
Keyword(s):  
Daily Living ◽  
Inertial Sensors ◽  
Wearable Sensors ◽  
Research Problem ◽  
Human Motion ◽  
Lower Limbs ◽  
Smart Devices ◽  
Joint Orientation ◽  
Human Actions ◽  
Living Environments

Action recognition is important for various applications, such as, ambient intelligence, smart devices, and healthcare. Automatic recognition of human actions in daily living environments, mainly using wearable sensors, is still an open research problem of the field of pervasive computing. This research focuses on extracting a set of features related to human motion, in particular the motion of the upper and lower limbs, in order to recognize actions in daily living environments, using time-series of joint orientation. Ten actions were performed by five test subjects in their homes: cooking, doing housework, eating, grooming, mouth care, ascending stairs, descending stairs, sitting, standing, and walking. The joint angles of the right upper limb and the left lower limb were estimated using information from five wearable inertial sensors placed on the back, right upper arm, right forearm, left thigh and left leg. The set features were used to build classifiers using three inference algorithms: Naive Bayes, K-Nearest Neighbours, and AdaBoost. The F- m e a s u r e average of classifying the ten actions of the three classifiers built by using the proposed set of features was 0.806 ( σ = 0.163).

scholarly journals Pre-Impact Detection Algorithm to Identify Tripping Events Using Wearable Sensors

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3713
Author(s):  
Federica Aprigliano ◽  
Silvestro Micera ◽  
Vito Monaco
Keyword(s):  
Wearable Sensors ◽  
Detection Algorithm ◽  
Lower Limbs ◽  
False Alarms ◽  
Daily Life Activities ◽  
Impact Detection ◽  
Wearable Robots ◽  
Adaptive Oscillators ◽  
Young Subjects ◽  
Smart Garments

This study aimed to investigate the performance of an updated version of our pre-impact detection algorithm parsing out the output of a set of Inertial Measurement Units (IMUs) placed on lower limbs and designed to recognize signs of lack of balance due to tripping. Eight young subjects were asked to manage tripping events while walking on a treadmill. An adaptive threshold-based algorithm, relying on a pool of adaptive oscillators, was tuned to identify abrupt kinematics modifications during tripping. Inputs of the algorithm were the elevation angles of lower limb segments, as estimated by IMUs located on thighs, shanks and feet. The results showed that the proposed algorithm can identify a lack of balance in about 0.37 ± 0.11 s after the onset of the perturbation, with a low percentage of false alarms (<10%), by using only data related to the perturbed shank. The proposed algorithm can hence be considered a multi-purpose tool to identify different perturbations (i.e., slippage and tripping). In this respect, it can be implemented for different wearable applications (e.g., smart garments or wearable robots) and adopted during daily life activities to enable on-demand injury prevention systems prior to fall impacts.

scholarly journals Health Index Monitoring of Sports Injury Rehabilitation Training Based on Wearable Sensors

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Jiang Yi ◽  
Yuepei Zou
Keyword(s):  
Human Body ◽  
Lower Limb ◽  
Wearable Sensors ◽  
Sports Injury ◽  
Human Motion ◽  
Lower Limbs ◽  
Angle Sensor ◽  
Perception System ◽  
Movement Mechanism ◽  
Analysis System

In order to design the perception system of the lower limb wearable rehabilitation robot, this study established the kinematics theoretical model of human lower limb and conducted the kinematics analysis of human body. By using the dynamic attitude analysis system, combined with the human body mark points, the position data of human body mark points in the process of standing up, sitting up, walking, stepping up, and squatting were collected. Combined with the movement mechanism of human lower limbs, the characteristics of human motion state transition are analyzed, and the perceptual algorithm for judging human motion intention is studied, so as to determine the wearer’s current posture, standing intention while sitting, walking intention while standing, moving intention, and stopping intention during walking. The results show that the angle of the hip joint changes regularly between 0° and 37° and the angle of the knee joint changes regularly between 0° and 70°during the standing process, which is consistent with the angle change trajectory collected by the dynamic attitude analysis system. The angle trajectories of the hip and knee joints measured by the absolute angle sensor are the same as those obtained by the dynamic attitude analysis system. 1.5 rad and 0.3 rad were selected as reasonable and effective thresholds for determining sitting and standing states.

Lower-Limb Rehabilitation at Home

2020 ◽  
Vol 12 (1) ◽  
pp. 15-27
Author(s):  
Seanglidet Yean ◽  
Bu Sung Lee ◽  
Chai Kiat Yeo
Keyword(s):  
Wearable Sensors ◽  
Initial Study ◽  
Lower Limbs ◽  
Support Vector ◽  
Machine Method ◽  
Average Accuracy ◽  
Sensor Signals ◽  
And Performance ◽  
The Impact ◽  
Rehabilitation Exercise

Aging causes loss of muscle strength, especially on the lower limbs, resulting in a higher risk of injuries during functional activities. To regain mobility and strength from injuries, physiotherapy prescribes rehabilitation exercise to assist the patients' recovery. In this article, the authors survey the existing work in exercise assessment and state identification which contributes to innovating the biofeedback for patient home guidance. The initial study on a machine-learning-based model is proposed to identify the 4-state motion of rehabilitation exercise using wearable sensors on the lower limbs. The study analyses the impact of the feature extracted from the sensor signals while classifying using the linear kernel of the support vector machine method. The evaluation results show that the method has an average accuracy of 95.83% using the raw sensor signal, which has more impact than the sensor fused Euler and joint angles in the state prediction model. This study will both enable real-time biofeedback and provide complementary support to clinical assessment and performance tracking.

Investigation of ferroelectrics using conventional and in situ electron microscopy

1994 ◽  
Vol 52 ◽  
pp. 586-587
Author(s):  
V. Saikumar ◽  
H. M. Chan ◽  
M. P. Harmer
Keyword(s):  
Nonvolatile Memory ◽  
Ferroelectric Materials ◽  
Gate Insulator ◽  
Sensors And Actuators ◽  
In Situ Electron Microscopy ◽  
Ferroelectric Domains ◽  
Domain Boundaries ◽  
Domain Interactions ◽  
Memory Applications

In recent years, there has been a growing interest in the application of ferroelectric thin films for nonvolatile memory applications and as a gate insulator in DRAM structures. In addition, bulk ferroelectric materials are also widely used as components in electronic circuits and find numerous applications in sensors and actuators. To a large extent, the performance of ferroelectric materials are governed by the ferroelectric domains (with dimensions in the micron to sub-micron range) and the switching of domains in the presence of an applied field. Conventional TEM studies of ferroelectric domains structures, in conjunction with in-situ studies of the domain interactions can aid in explaining the behavior of ferroelectric materials, while providing some answers to the mechanisms and processes that influence the performance of ferroelectric materials. A few examples from bulk and thin film ferroelectric materials studied using the TEM are discussed below.Figure 1 shows micrographs of ferroelectric domains obtained from undoped and Fe-doped BaTiO3 single crystals. The domain boundaries have been identified as 90° domains with the boundaries parallel to <011>.

Mid-aortic syndrome: computed tomography angiography depicting extensive collateral circulation in an 11-year-old patient with thoracoabdominal aortic coarctation

VASA ◽  
2012 ◽  
Vol 41 (2) ◽  
pp. 132-135 ◽  
Author(s):  
Krohn ◽  
Gebauer ◽  
Hübler ◽  
Beck
Keyword(s):  
Computed Tomography ◽  
Computed Tomography Angiography ◽  
Collateral Circulation ◽  
Intestinal Ischemia ◽  
Clinical Presentation ◽  
Lower Limbs ◽  
Upper Body ◽  
Descending Aorta ◽  
Before And After ◽  
Blood Pressures

The mid-aortic syndrome is an uncommon clinical condition characterized by severe narrowing of the descending aorta, usually with involvement of its renal and visceral branches, presenting with uncontrollably elevated blood pressures of the upper body, renal and cardiac failure, intestinal ischemia, encephalopathy symptoms and claudication of the lower limbs, although clinical presentation is variable. In this article we report the case of an eleven-year-old patient with the initial diagnosis of a mid-aortic syndrome and present the computed tomography angiography pictures and reconstructions before and after surgical therapy.

Comparison of standardised lymphoscintigraphic function test and high resolution sonography of the lymphoedema of legs

Phlebologie ◽  
2008 ◽  
Vol 37 (05) ◽  
pp. 247-252 ◽  
Author(s):  
V. S. Brauer ◽  
W. J. Brauer
Keyword(s):  
Lower Leg ◽  
Clinical Findings ◽  
Lower Limbs ◽  
Fatty Tissue ◽  
Qualitative And Quantitative ◽  
Function Test ◽  
Unreliable Method ◽  
Negative Conclusion ◽  
Fine Disperse

SummaryPurpose: Comparison of qualitative and quantitative sonography with the lymphoscintigraphic function test and clinical findings in legs. Patients, methods: In 33 patients a lymphoscintigraphic function test of legs combined with measurement of lymph node uptake was performed and subsequently compared with sonography. Sonographic criteria were: Thickness of cutis, thickness of subcutanean fatty tissue and presence of liquid structures or fine disperse tissue structure of lower limbs, foots and toes. Results: In 51 legs uptake values lie in the pathologic area, in four legs in the grey area and in ten legs in the normal area. The cutis thickness in the lower leg shows no significant correlation with the uptake. The determination of the thickness of the subcutanean fatty tissue of the lower leg and of the cutis thickness of the feet turned out to be an unreliable method. In 47% of the medial lower legs and in 57% of the lateral lower legs with clinical lymphoedema sonography is falsely negative. Conclusion: Early lymphoedema is only detectable with the lymphoscintigraphic function test. In the case of clinical lymphoedema clinical examination is more reliable than sonography.

Sign in / Sign up

Export Citation Format

Share Document