scholarly journals Evaluation of Joint Motion Sensing Efficiency According to the Implementation Method of SWCNT-Coated Fabric Motion Sensor

Sensors ◽  
2020 ◽  
Vol 20 (1) ◽  
pp. 284 ◽  
Author(s):  
Hyun-Seung Cho ◽  
Jin-Hee Yang ◽  
Jeong-Hwan Lee ◽  
Joo-Hyeon Lee
Keyword(s):  
Motion Sensor ◽  
Joint Motion ◽  
Motion Sensors ◽  
Motion Sensing ◽  
Piezoresistive Sensors ◽  
Piezoresistive Sensor ◽  
Acceleration Sensors ◽  
Flexion Extension ◽  
Joint Motions ◽  
Walled Carbon Nanotubes

The purpose of this study was to investigate the effects of the shape and attachment position of stretchable textile piezoresistive sensors coated with single-walled carbon nanotubes on their performance in measuring the joint movements of children. The requirements for fabric motion sensors suitable for children are also identified. The child subjects were instructed to wear integrated clothing with sensors of different shapes (rectangular and boat-shaped), attachment positions (at the knee and elbow joints or 4 cm below the joints). The change in voltage caused by the elongation and contraction of the fabric sensors was measured for the flexion-extension motions of the arms and legs at 60°/s (three measurements of 10 repetitions each for the 60° and 90° angles, for a total of 60 repetitions). Their reliability was verified by analyzing the agreement between the fabric motion sensors and attached acceleration sensors. The experimental results showed that the fabric motion sensor that can measure children’s arm and leg motions most effectively is the rectangular-shaped sensor attached 4 cm below the joint. In this study, we developed a textile piezoresistive sensor suitable for measuring the joint motion of children, and analyzed the shape and attachment position of the sensor on clothing suitable for motion sensing. We showed that it is possible to sense joint motions of the human body by using flexible fabric sensors integrated into clothing.

scholarly journals Conditions for CNT – Coated Textile Sensors Applied to Wearable Platforms to Monitor Limb Joint Motion

2021 ◽  
Vol 45 (4) ◽  
Author(s):  
Da-Hye Kang ◽  
Joo-Hyeon Lee ◽  
Jeong-Whan Lee ◽  
Hyun-Seung Cho ◽  
Seon-Hyung Park ◽  
...  
Keyword(s):  
Human Body ◽  
Body Movement ◽  
Measurement Techniques ◽  
Joint Motion ◽  
Motion Sensors ◽  
Large Space ◽  
Motion Measurement ◽  
Sensor Structure ◽  
Textile Sensors ◽  
Joint Motions

AbstractDespite recent research on joint motion measurement to monitor human body movement, current measurement techniques and tools have significant limitations, including requiring large space for measurement and causing discomfort in test subjects wearing motion sensors. Our study aims, first, to develop carbon nanotube (CNT)-based textile joint motion sensors. Second, ours study aims to identify the most suitable CNT-based sensor structure and attachment method for use on a wearable platform during general exercise speeds. Lastly, we used these sensors on the human body, using sleeves and legs to find the most stable location, and we used the CNT-based sensor condition to monitor joint motions. We utilized our CNT-based sensor, which has proper elasticity as well as conductivity, and applied it to the elbow and knee joints. Based on the strain gauge principle, we monitored the variance of electric resistance that occurred when the CNT-based sensor was stretched due to limb motion. Our study tested 48 types of sensors. These sensors were applied to the CNT using different base knit textiles as well as different attachment methods, layers, sensor lengths, and sensor widths. The four most successful sensor types, which showed superior efficacy over the others in joint motion measurement, were selected for further study. These four sensors were then used to measure the elbow and knee joint motions of human subjects by placing them on different locations on sleeves and legs. The CNT knit textile sensors best suited to measuring joint motions are those with a double-layered CNT knit and 5 cm long × 0.5 cm or 1 cm wide sensors attached to a polyester¬-based knit using a welding method. The best position for the sensor to more stably monitor joint motions was the “below hinge position” from the elbow or knee hinge joint. Our study suggests an alternative strategy for joint-motion measurement that could contribute to the development of more comfortable and human-friendly methods of human limb motion measurement.

scholarly journals Quantifying Habitual Physical Activity and Sedentariness in Older Adults—Different Outcomes of Two Simultaneously Body-Worn Motion Sensor Approaches and a Self-Estimation

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1877
Author(s):  
Rieke Trumpf ◽  
Wiebren Zijlstra ◽  
Peter Haussermann ◽  
Tim Fleiner
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Community Dwelling ◽  
Habitual Physical Activity ◽  
Motion Sensor ◽  
Motion Sensors ◽  
Healthy Older Adults ◽  
Lower Back ◽  
Hybrid Motion ◽  
Accurate Quantification

Applicable and accurate assessment methods are required for a clinically relevant quantification of habitual physical activity (PA) levels and sedentariness in older adults. The aim of this study is to compare habitual PA and sedentariness, as assessed with (1) a wrist-worn actigraph, (2) a hybrid motion sensor attached to the lower back, and (3) a self-estimation based on a questionnaire. Over the course of one week, PA of 58 community-dwelling subjectively healthy older adults was recorded. The results indicate that actigraphy overestimates the PA levels in older adults, whereas sedentariness is underestimated when compared to the hybrid motion sensor approach. Significantly longer durations (hh:mm/day) for all PA intensities were assessed with the actigraph (light: 04:19; moderate to vigorous: 05:08) when compared to the durations (hh:mm/day) that were assessed with the hybrid motion sensor (light: 01:24; moderate to vigorous: 02:21) and the self-estimated durations (hh:mm/day) (light: 02:33; moderate to vigorous: 03:04). Actigraphy-assessed durations of sedentariness (14:32 hh:mm/day) were significantly shorter when compared to the durations assessed with the hybrid motion sensor (20:15 hh:mm/day). Self-estimated duration of light intensity was significantly shorter when compared to the results of the hybrid motion sensor. The results of the present study highlight the importance of an accurate quantification of habitual PA levels and sedentariness in older adults. The use of hybrid motion sensors can offer important insights into the PA levels and PA types (e.g., sitting, lying) and it can increase the knowledge about mobility-related PA and patterns of sedentariness, while actigraphy appears to be not recommendable for this purpose.

Highly accurate fabric piezoresistive sensor with anti-interference of both high humidity and sweat based on hydrophobic non-fluoride titanium dioxide nanoparticle

2021 ◽  
Author(s):  
Liyan Yang ◽  
Jun Ma ◽  
Weibing Zhong ◽  
Qiongzhen Liu ◽  
Mu fang Li ◽  
...  
Keyword(s):  
Titanium Dioxide ◽  
Conductive Polymers ◽  
Human Motion ◽  
High Humidity ◽  
Titanium Dioxide Nanoparticle ◽  
Piezoresistive Sensors ◽  
Piezoresistive Sensor

The fabric-based piezoresistive sensors have demonstrated great potentials in the application of human motion and health detection. However, the conductive polymers of the sensing units are easily influenced by high...

Reverse Electrowetting-on-Dielectric Energy Harvesting Integrated With Charge Amplifier and Rectifier for Self-Powered Motion Sensors

2020 ◽  
Author(s):  
Pashupati R. Adhikari ◽  
Nishat T. Tasneem ◽  
Dipon K. Biswas ◽  
Russell C. Reid ◽  
Ifana Mahbub
Keyword(s):  
Energy Harvester ◽  
Schottky Diodes ◽  
Boost Converter ◽  
Motion Sensor ◽  
Motion Sensors ◽  
Frequency Range ◽  
Charge Amplifier ◽  
Electrowetting On Dielectric ◽  
Dc Voltage ◽  
Self Powered

Abstract This paper presents a reverse electrowetting-on-dielectric (REWOD) energy harvester integrated with rectifier, boost converter, and charge amplifier that is, without bias voltage, capable of powering wearable sensors for monitoring human health in real-time. REWOD has been demonstrated to effectively generate electrical current at a low frequency range (< 3 Hz), which is the frequency range for various human activities such as walking, running, etc. However, the current generated from the REWOD without external bias source is insufficient to power such motion sensors. In this work, to eventually implement a fully self-powered motion sensor, we demonstrate a novel bias-free REWOD AC generation and then rectify, boost, and amplify the signal using commercial components. The unconditioned REWOD output of 95–240 mV AC is generated using a 50 μL droplet of 0.5M NaCl electrolyte and 2.5 mm of electrode displacement from an oscillation frequency range of 1–3 Hz. A seven-stage rectifier using Schottky diodes having a forward voltage drop of 135–240 mV and a forward current of 1 mA converts the generated AC signal to DC voltage. ∼3 V DC is measured at the boost converter output, proving the system could function as a self-powered motion sensor. Additionally, a linear relationship of output DC voltage with respect to frequency and displacement demonstrates the potential of this REWOD energy harvester to function as a self-powered wearable motion sensor.

scholarly journals Assessing the Mobility of Elderly People in Domestic Smart Home Environments

2020 ◽  
Author(s):  
Björn Friedrich ◽  
Enno-Edzard Steen ◽  
Sebastian Fudickar ◽  
Andreas Hein
Keyword(s):  
Elderly People ◽  
Smart Home ◽  
Continuous Monitoring ◽  
Early Stage ◽  
Motion Sensor ◽  
Motion Sensors ◽  
Physical Strength ◽  
Assessment Scores ◽  
Mobility Assessment ◽  
Smart Home Environments

A continuous monitoring of the physical strength and mobility of elderly people is important for maintaining their health and treating diseases at an early stage. However, frequent screenings by physicians are exceeding the logistic capacities. An alternate approach is the automatic and unobtrusive collection of functional measures by ambient sensors. In the current publication, we show the correlation among data of ambient motion sensors and the wellestablished mobility assessment Short-Physical-Performance-Battery and Tinetti. We use the average number of motion sensor events for correlation with the assessment scores. The evaluation on a real-world dataset shows a moderate to strong correlation with the scores of standardised geriatrics physical assessments.

A Novel Training Bike and Camera System to Evaluate Pose of Cyclists

2020 ◽  
Author(s):  
Raman Garimella ◽  
Koen Beyers ◽  
Thomas Peeters ◽  
Stijn Verwulgen ◽  
Seppe Sels ◽  
...  
Keyword(s):  
Inertial Sensors ◽  
Sagittal Plane ◽  
Aerodynamic Drag ◽  
Linear Regression Analysis ◽  
The Body ◽  
Frontal Area ◽  
Motion Sensors ◽  
Joint Angles ◽  
Camera System ◽  
Flexion Extension

Abstract Aerodynamic drag force can account for up to 90% of the opposing force experienced by a cyclist. Therefore, aerodynamic testing and efficiency is a priority in cycling. An inexpensive method to optimize performance is required. In this study, we evaluate a novel indoor setup as a tool for aerodynamic pose training. The setup consists of a bike, indoor home trainer, camera, and wearable inertial motion sensors. A camera calculates frontal area of the cyclist and the trainer varies resistance to the cyclist by using this as an input. To guide a cyclist to assume an optimal pose, joint angles of the body are an objective metric. To track joint angles, two methods were evaluated: optical (RGB camera for the two-dimensional angles in sagittal plane of 6 joints), and inertial sensors (wearable sensors for three-dimensional angles of 13 joints). One (1) male amateur cyclist was instructed to recreate certain static and dynamic poses on the bike. The inertial sensors provide excellent results (absolute error = 0.28°) for knee joint. Based on linear regression analysis, frontal area can be best predicted (correlation > 0.4) by chest anterior/posterior tilt, pelvis left/right rotation, neck flexion/extension, chest left/right rotation, and chest left/right lateral tilt (p < 0.01).

scholarly journals A Hierarchical Deep Fusion Framework for Egocentric Activity Recognition Using a Wearable Hybrid Sensor System

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 546 ◽  
Author(s):  
Haibin Yu ◽  
Guoxiong Pan ◽  
Mian Pan ◽  
Chong Li ◽  
Wenyan Jia ◽  
...  
Keyword(s):  
Activity Recognition ◽  
Short Term Memory ◽  
Specific Activity ◽  
Negative Influence ◽  
Sensor System ◽  
Sensor Data ◽  
Motion Sensor ◽  
Motion Sensors ◽  
Motion State ◽  
Fusion Framework

Recently, egocentric activity recognition has attracted considerable attention in the pattern recognition and artificial intelligence communities because of its wide applicability in medical care, smart homes, and security monitoring. In this study, we developed and implemented a deep-learning-based hierarchical fusion framework for the recognition of egocentric activities of daily living (ADLs) in a wearable hybrid sensor system comprising motion sensors and cameras. Long short-term memory (LSTM) and a convolutional neural network are used to perform egocentric ADL recognition based on motion sensor data and photo streaming in different layers, respectively. The motion sensor data are used solely for activity classification according to motion state, while the photo stream is used for further specific activity recognition in the motion state groups. Thus, both motion sensor data and photo stream work in their most suitable classification mode to significantly reduce the negative influence of sensor differences on the fusion results. Experimental results show that the proposed method not only is more accurate than the existing direct fusion method (by up to 6%) but also avoids the time-consuming computation of optical flow in the existing method, which makes the proposed algorithm less complex and more suitable for practical application.

Control System for an Elbow Joint Motion Simulator

2007 ◽  
Author(s):  
Patrick J. Schimoler ◽  
Jeffrey S. Vipperman ◽  
Laurel Kuxhaus ◽  
Angela M. Flamm ◽  
Daniel D. Budny ◽  
...  
Keyword(s):  
Control System ◽  
Elbow Joint ◽  
Degrees Of Freedom ◽  
Biceps Brachii ◽  
Control Algorithms ◽  
Joint Motion ◽  
Motion Simulator ◽  
Co Activation ◽  
Flexion Extension ◽  
The Many

The many muscles crossing the elbow joint allow for its motions to be created from different combinations of muscular activations. Muscles are strictly contractile elements and the joints they surround rely on varying loads from opposing antagonists for stability and movement. In designing a control system to actuate an elbow in a realistic manner, unidirectional, tendon-like actuation and muscle co-activation must be considered in order to successfully control the elbow’s two degrees of freedom. Also important is the multifunctionality of certain muscles, such as the biceps brachii, which create moments impacting both degrees of freedom: flexion / extension and pronation / supination. This paper seeks to develop and implement control algorithms on an elbow joint motion simulator that actuates cadaveric elbow specimens via four major muscles that cross the elbow joint. The algorithms were validated using an anatomically-realistic mechanical elbow. Clinically-meaningful results, such as the evaluation of radial head implants, can only be obtained under repeatable, realistic conditions; therefore, physiologic motions must be created by the application of appropriate loads. This is achieved by including load control on the muscles’ actuators as well as displacement control on both flexion / extension and supination / pronation.

Transient—Sustained Input to Directionally Selective Motion Mechanisms

Perception ◽  
1996 ◽  
Vol 25 (11) ◽  
pp. 1263-1280 ◽  
Author(s):  
Walter F Bischof ◽  
Adriane E Seiffert ◽  
Vincent Di Lollo
Keyword(s):  
Apparent Motion ◽  
Motion Sensor ◽  
Motion Sensors ◽  
Single Image ◽  
High Luminance ◽  
New Model ◽  
Low Luminance ◽  
Directional Motion ◽  
Combined Images ◽  
Psychophysical Studies

The characteristics of the sustained input to directionally selective motion sensors were examined in three human psychophysical studies on directional-motion discrimination. Apparent motion was produced by displaying a group of dots in two frames (F1 and F2), where F2 was a translated version of F1. All stimuli included parts that contained both F1 and F2 (combined images) and parts containing only F1 or F2 (single images). All displays began with a single image (F1), continued with the combined image, and ended with F2. Six durations of single and of combined images (10, 20, 40, 80, 160, or 320 ms) were crossed factorially. As the duration of the single image was increased, perception of directional motion first improved, and then declined at longer durations. This outcome contrasted with the monotonic increment obtained in earlier studies under low-luminance conditions. To account for the entire pattern of results, earlier models of the Reichardt motion sensor were modified so as to include a mixed transient – sustained input to one of the filters of the sensor. Predictions from the new model were tested and confirmed in two experiments carried out under both low-luminance and high-luminance viewing conditions.

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