Synthetized inertial measurement units (IMUs) to evaluate the placement of wearable sensors on human body for motion recognition

Hoareau, Damien; Jodin, Gurvan; Chantal, Pierre‐Antoine; Bretin, Sara; Prioux, Jacques; Razan, Florence

doi:10.1049/tje2.12137

Cited by 7 publications

(4 citation statements)

References 16 publications

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“…Therefore, to better understand the differences in the abilities of IMU and VICON Nexus kinematic modelling in analysing the LyE, examining the same variable is required. Between-session differences were also present in IMU shank acceleration, potentially due to the orientation of the tibia, making it more subject to skin and flesh artefacts [ 65 ]. However, IMUs were placed just below the tibial tuberosity to best ensure placement consistency [ 19 ].…”

Section: Discussionmentioning

confidence: 99%

Analysis of Movement Variability in Cycling: An Exploratory Study

Winter

Bellenger

Grimshaw

et al. 2023

Sensors

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The purpose of this study was to determine the test-retest repeatability of Blue Trident inertial measurement units (IMUs) and VICON Nexus kinematic modelling in analysing the Lyapunov Exponent (LyE) during a maximal effort 4000 m cycling bout in different body segments/joints. An additional aim was to determine if changes in the LyE existed across a trial. Twelve novice cyclists completed four sessions of cycling; one was a familiarisation session to determine a bike fit and become better accustomed to the time trial position and pacing of a 4000 m effort. IMUs were attached to the head, thorax, pelvis and left and right shanks to analyse segment accelerations, respectively, and reflective markers were attached to the participant to analyse neck, thorax, pelvis, hip, knee and ankle segment/joint angular kinematics, respectively. Both the IMU and VICON Nexus test-retest repeatability ranged from poor to excellent at the different sites. In each session, the head and thorax IMU acceleration LyE increased across the bout, whilst pelvic and shank acceleration remained consistent. Differences across sessions were evident in VICON Nexus segment/joint angular kinematics, but no consistent trend existed. The improved reliability and the ability to identify a consistent trend in performance, combined with their improved portability and reduced cost, advocate for the use of IMUs in analysing movement variability in cycling. However, additional research is required to determine the applicability of analysing movement variability during cycling.

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Section: Discussionmentioning

confidence: 99%

Analysis of Movement Variability in Cycling: An Exploratory Study

Winter

Bellenger

Grimshaw

et al. 2023

Sensors

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“…), and they allow detection of bending angle, linear 3D acceleration, three-dimensional orientation, and angular velocity to track joint movements, walking speed, etc. ( Figure 6 a) [ 75 , 76 , 77 , 78 ]. Moreover, an additional advantage of IMU is the capacity to measure a patient’s or an athlete’s energy consumption—critical for determining, for example, the intensity of the training—by multiple integrations of vertical acceleration over time.…”

Section: Transduction Mechanisms For the Acquisition Of Human Paramet...mentioning

confidence: 99%

Wearable Sensors and Smart Devices to Monitor Rehabilitation Parameters and Sports Performance: An Overview

Fazio

Mastronardi

Vittorio

et al. 2023

Sensors

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A quantitative evaluation of kinetic parameters, the joint’s range of motion, heart rate, and breathing rate, can be employed in sports performance tracking and rehabilitation monitoring following injuries or surgical operations. However, many of the current detection systems are expensive and designed for clinical use, requiring the presence of a physician and medical staff to assist users in the device’s positioning and measurements. The goal of wearable sensors is to overcome the limitations of current devices, enabling the acquisition of a user’s vital signs directly from the body in an accurate and non–invasive way. In sports activities, wearable sensors allow athletes to monitor performance and body movements objectively, going beyond the coach’s subjective evaluation limits. The main goal of this review paper is to provide a comprehensive overview of wearable technologies and sensing systems to detect and monitor the physiological parameters of patients during post–operative rehabilitation and athletes’ training, and to present evidence that supports the efficacy of this technology for healthcare applications. First, a classification of the human physiological parameters acquired from the human body by sensors attached to sensitive skin locations or worn as a part of garments is introduced, carrying important feedback on the user’s health status. Then, a detailed description of the electromechanical transduction mechanisms allows a comparison of the technologies used in wearable applications to monitor sports and rehabilitation activities. This paves the way for an analysis of wearable technologies, providing a comprehensive comparison of the current state of the art of available sensors and systems. Comparative and statistical analyses are provided to point out useful insights for defining the best technologies and solutions for monitoring body movements. Lastly, the presented review is compared with similar ones reported in the literature to highlight its strengths and novelties.

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“…In service operations, a two-level filtering strategy is used to determine the optimal resolution of RCaaS based on the processing user's index preferences, functional, and non functional requirements. The entire structure includes decision support, centralized, and integrated control [12].…”

Section: Interactive Control Frameworkmentioning

confidence: 99%

Exploration on Target Object Recognition and Location Technology of Mobile Robot Based on Digital Twin

Hou¹

2023

Preprint

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In recent years, robot technology has developed rapidly. With the continuous progress and innovation of technology, intelligent mobile robots have become a very common technical element in life. Mobile robot target recognition is a multidisciplinary and complex technology based on image processing, analysis, and understanding, which has great application value and importance. Digital Twin technology provides services, data, and information and physical space can be integrated and displayed through the connection of analog models and physical devices. Therefore, there is an urgent need to study the concept of digital twins and combine them with digital robots to identify and identify targets. In this paper, digital twinning technology was applied to mobile robots to study target recognition and positioning technology. This article constructed a mobile robot digital twin system, and introduced the interactive control framework of the digital twin mobile robot and the virtual real interaction mechanism. The overall framework and operation mechanism of the mobile robot digital twin system have been basically established. After taking photos of the target, the minimum variance filtering algorithm was used for image processing. The threshold segmentation algorithm was used to segment the processed image, and then the directional gradient histogram method was used to extract image features. Finally, SVM (Support Vector Machine) classifier was used to classify images based on the extracted image features, so as to achieve the goal of target object recognition. After completing target object recognition, EKF (Extended Kalman Filter) was used to locate the target object, thereby achieving target object positioning. The experimental part carried out target object recognition and positioning. The experimental results showed that the digital twin mobile robot had a high effect on target object recognition and positioning, with an accuracy rate of over 80% for target object recognition. The x-axis and y-axis positioning errors of the digital twin mobile robot were lower than traditional positioning algorithms, and could effectively identify and locate target objects.

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Synthetized inertial measurement units (IMUs) to evaluate the placement of wearable sensors on human body for motion recognition

Cited by 7 publications

References 16 publications

Analysis of Movement Variability in Cycling: An Exploratory Study

Analysis of Movement Variability in Cycling: An Exploratory Study

Wearable Sensors and Smart Devices to Monitor Rehabilitation Parameters and Sports Performance: An Overview

Exploration on Target Object Recognition and Location Technology of Mobile Robot Based on Digital Twin

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