Validation of a Wireless Sensor System for the Estimation of Cumulative Lumbar Loads in Occupational Settings

2021 ◽  
Vol 65 (1) ◽  
pp. 489-494
Author(s):  
Ivan Nail-Ulloa ◽  
Sean Gallagher ◽  
Rong Huangfu ◽  
Dania Bani-Hani ◽  
Nathan Pool
Keyword(s):  
Repeated Measures ◽  
Sensor System ◽  
Wireless Sensor ◽  
Close Correspondence ◽  
Manual Lifting ◽  
Moment Estimates ◽  
Optical Motion ◽  
Optical Motion Capture ◽  
Occupational Settings ◽  
Laboratory Models

This study aimed to evaluate the accuracy of 3D L5/S1 moment estimates from a wearable inertial motioncapture system during manual lifting tasks. Reference L5/S1 moments were calculated using inversedynamics bottom-up and top-down laboratory models, based on the data from a measurement systemcomprising optical motion capture and force plates. Nine groups of four subjects performed tasks consistingof lifting and lowering 10 lbs. load with three different heights and asymmetry angles. As a measure ofsystem performance, the root means square errors and absolute peak errors between models werecompared. Also, repeated measures analyses of variance were calculated comparing the means and theabsolute peaks of the estimated moments. The results suggest that most of the estimates obtained from thewireless sensor system are in close correspondence when comparing the means, and more variability isobserved when comparing peak values to other models calculating estimates of L5/S1 moments.

scholarly journals The Influence of Backpack Weight and Hip Belt Tension on Movement and Loading in the Pelvis and Lower Limbs during Walking

2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
Katja Oberhofer ◽  
Patrick D. Wettenschwiler ◽  
Navrag Singh ◽  
Stephen J. Ferguson ◽  
Simon Annaheim ◽  
...  
Keyword(s):  
Repeated Measures ◽  
Lower Limbs ◽  
Gait Biomechanics ◽  
Flexion Extension ◽  
Optical Motion ◽  
Reaction Forces ◽  
Optical Motion Capture ◽  
Post Hoc ◽  
Male Subjects ◽  
Backpack Weight

The introduction of hip belts to backpacks has caused a shift of loading from the spine to the hips with reported improvements in musculoskeletal comfort. Yet the effects of different hip belt tensions on gait biomechanics remain largely unknown. The goal of this study was to assess the influence of backpack weight and hip belt tension on gait biomechanics. Data from optical motion capture and ground reaction forces (GRF) during walking were acquired in nine healthy male subjects (age 28.0 ± 3.9 years). Six configurations of a commercial backpack were analyzed, that is, 15 kg, 20 kg, and 25 kg loading with 30 N and 120 N hip belt tension. Joint ranges of motion (ROM), peak GRF, and joint moments during gait were analyzed for significant differences by repeated measures of ANOVA with Bonferroni post hoc comparison. Increased loading led to a significant reduction of knee flexion-extension ROM as well as pelvis rotational ROM. No statistically significant effect of hip belt tension magnitudes on gait dynamics was found at any backpack weight, yet there was a trend of increased pelvis ROM in the transverse plane with higher hip belt tension at 25 kg loading. Further research is needed to elucidate the optimum hip belt tension magnitudes for different loading weights to reduce the risks of injury especially with higher loading.

Effects of Camera Switching on Fine Accuracy in a Motion Capture System

2008 ◽  
Vol 131 (1) ◽  
Author(s):  
Laurel Kuxhaus ◽  
Patrick J. Schimoler ◽  
Jeffrey S. Vipperman ◽  
Mark Carl Miller
Keyword(s):  
Motion Capture ◽  
Radial Head ◽  
Repeated Measures ◽  
Random Noise ◽  
Simulated Data ◽  
User Interaction ◽  
Motion Capture System ◽  
Optical Motion ◽  
Analysis System ◽  
Optical Motion Capture

When using optical motion capture systems, increasing the number of cameras improves the visibility. However, the software used to deal with the information fusion from multiple cameras may compromise the accuracy of the system due to camera dropout, which can vary with time. In cadaver studies of radial head motion, increasing the number of cameras used by the motion capture system seemed to decrease the accuracy of the measurements. This study investigates the cause. The hypothesis was that errors in position can be induced when markers are obscured from and then restored to a camera’s viewable range, as can happen in biomechanical studies. Accuracy studies quantified the capabilities of the motion capture system with precision translation and rotation movements. To illustrate the effect that abrupt perceived changes in a marker’s position can have on the calculation of radial head travel, simulated motion experiments were performed. In these studies, random noise was added to simulated data, which obscured the resultant path of motion. Finally, camera-blocking experiments were performed in which precise movements were measured with a six-camera Vicon system and the errors between the actual and perceived motion were computed. During measurement, cameras were selectively blocked and restored to view. The maximum errors in translation and rotation were 3.7 mm and 0.837 deg, respectively. Repeated measures analysis of variance (ANOVAs) (α=0.05) confirmed that the camera-blocking influenced the results. Taken together, these results indicate that camera-switching can affect the observation of fine movements using a motion analysis system with a large number of cameras. One solution is to offer opportunity for user interaction in the software to choose the cameras used for each instant of time.

scholarly journals Patch-Type Vibration Visualization (PVV) Sensor System Based on Triboelectric Effect

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3976
Author(s):  
Sun Jin Kim ◽  
Myeong-Lok Seol ◽  
Byun-Young Chung ◽  
Dae-Sic Jang ◽  
Jonghwan Kim ◽  
...  
Keyword(s):  
Signal Processing ◽  
Low Power ◽  
Nuclear Power ◽  
Power Plants ◽  
Computing System ◽  
Sensor System ◽  
Wireless Sensor ◽  
Sensor Systems ◽  
Patch Type ◽  
Triboelectric Effect

Self-powered wireless sensor systems have emerged as an important topic for condition monitoring in nuclear power plants. However, commercial wireless sensor systems still cannot be fully self-sustainable due to the high power consumption caused by excessive signal processing in a mini-electronic computing system. In this sense, it is essential not only to integrate the sensor system with energy-harvesting devices but also to develop simple data processing methods for low power schemes. In this paper, we report a patch-type vibration visualization (PVV) sensor system based on the triboelectric effect and a visualization technique for self-sustainable operation. The PVV sensor system composed of a polyethylene terephthalate (PET)/Al/LCD screen directly converts the triboelectric signal into an informative black pattern on the LCD screen without excessive signal processing, enabling extremely low power operation. In addition, a proposed image processing method reconverts the black patterns to frequency and acceleration values through a remote-control camera. With these simple signal-to-pattern conversion and pattern-to-data reconversion techniques, a vibration visualization sensor network has successfully been demonstrated.

scholarly journals Sensor System: A Survey of Sensor Type, Ad Hoc Network Topology and Energy Harvesting Techniques

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 219
Author(s):  
Phuoc Duc Nguyen ◽  
Lok-won Kim
Keyword(s):  
Energy Harvesting ◽  
Large Scale ◽  
Ad Hoc ◽  
Sensor Nodes ◽  
Sensor System ◽  
Wireless Sensor ◽  
The Internet ◽  
Original Research ◽  
Energy Scavenging ◽  
Term Operation

People nowadays are entering an era of rapid evolution due to the generation of massive amounts of data. Such information is produced with an enormous contribution from the use of billions of sensing devices equipped with in situ signal processing and communication capabilities which form wireless sensor networks (WSNs). As the number of small devices connected to the Internet is higher than 50 billion, the Internet of Things (IoT) devices focus on sensing accuracy, communication efficiency, and low power consumption because IoT device deployment is mainly for correct information acquisition, remote node accessing, and longer-term operation with lower battery changing requirements. Thus, recently, there have been rich activities for original research in these domains. Various sensors used by processing devices can be heterogeneous or homogeneous. Since the devices are primarily expected to operate independently in an autonomous manner, the abilities of connection, communication, and ambient energy scavenging play significant roles, especially in a large-scale deployment. This paper classifies wireless sensor nodes into two major categories based the types of the sensor array (heterogeneous/homogeneous). It also emphasizes on the utilization of ad hoc networking and energy harvesting mechanisms as a fundamental cornerstone to building a self-governing, sustainable, and perpetually-operated sensor system. We review systems representative of each category and depict trends in system development.

scholarly journals An Intelligent In-Shoe System for Gait Monitoring and Analysis with Optimized Sampling and Real-Time Visualization Capabilities

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2869
Author(s):  
Jiaen Wu ◽  
Kiran Kuruvithadam ◽  
Alessandro Schaer ◽  
Richie Stoneham ◽  
George Chatzipirpiridis ◽  
...  
Keyword(s):  
Real Time ◽  
Inertial Sensor ◽  
Neurological Diseases ◽  
Principal Component ◽  
Sampling Frequency ◽  
Powerful Analytical Tool ◽  
Optical Motion ◽  
Analysis System ◽  
Optical Motion Capture ◽  
Gait Monitoring

The deterioration of gait can be used as a biomarker for ageing and neurological diseases. Continuous gait monitoring and analysis are essential for early deficit detection and personalized rehabilitation. The use of mobile and wearable inertial sensor systems for gait monitoring and analysis have been well explored with promising results in the literature. However, most of these studies focus on technologies for the assessment of gait characteristics, few of them have considered the data acquisition bandwidth of the sensing system. Inadequate sampling frequency will sacrifice signal fidelity, thus leading to an inaccurate estimation especially for spatial gait parameters. In this work, we developed an inertial sensor based in-shoe gait analysis system for real-time gait monitoring and investigated the optimal sampling frequency to capture all the information on walking patterns. An exploratory validation study was performed using an optical motion capture system on four healthy adult subjects, where each person underwent five walking sessions, giving a total of 20 sessions. Percentage mean absolute errors (MAE%) obtained in stride time, stride length, stride velocity, and cadence while walking were 1.19%, 1.68%, 2.08%, and 1.23%, respectively. In addition, an eigenanalysis based graphical descriptor from raw gait cycle signals was proposed as a new gait metric that can be quantified by principal component analysis to differentiate gait patterns, which has great potential to be used as a powerful analytical tool for gait disorder diagnostics.

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