Inertial Sensor-to-Segment Calibration for Accurate 3D Joint Angle Calculation for Use in OpenSim

Raimondo, G. Di; Vanwanseele, Benedicte; Have, Arthur van der; Emmerzaal, Jill; Willems, M.; Killen, Bryce A.; Jonkers, Ilse

doi:10.3390/s22093259

Cited by 18 publications

(30 citation statements)

References 81 publications

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“…At present, most of the display screens on the market are manually adjusted or use a physical method to maintain the height of the screen, and it is impossible to adjust the user's state at any time [7][8][9]. The lifting frame of the adjustable liquid crystal display (LCD) screen can flexibly adjust the height of the LCD screen and obtain a comfortable experience of using the computer.…”

Section: Introductionmentioning

confidence: 99%

Design of Active Display Stand Combing the Pressure Sensor and Kinematics Algorithm

Lei

2022

Journal of Sensors

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To solve the trouble of cervical vertebra disease caused by long working hours, this work is aimed at designing an active monitor stand to achieve the best dynamic trajectory planning. The stand operation system consists of image input, face positioning, and robotic arm. According to the user’s face positioning, the inverse kinematics method is used to calculate the steering angle in each direction, and the height and angle are adjusted to make the corresponding selection for the user’s display position on the screen. The C++ is used to program the algorithm, and its core is to control the rotation speed of the motor to ensure that the display screen will not cause any interference to the normal work of the user when the bracket moves. In the inverse operation, the Piper method is used to solve the inverse kinematics issues. After testing, the sliding wedge stroke of the developed active display stand is 0.6 mm, and the height position difference at the reference zero point after the display stand is measured with a digital altimeter is 7.12 mm, which indicates that the stand shows a large deformation after being mounted. This work is of important reference value for realizing the movement of active display stand.

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Section: Introductionmentioning

confidence: 99%

Design of Active Display Stand Combing the Pressure Sensor and Kinematics Algorithm

Lei

2022

Journal of Sensors

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“…As for clinic practice, there are also obstacles. Direct correlation between clusters groups (received by gait data) and injuries or diseases does not always appear [ 15 , 33 ]. Studies offer ways to meet the challenges: increase data, increase number of gait phases, etc.…”

Section: Resultsmentioning

confidence: 99%

The Automatization of the Gait Analysis by the Vicon Video System: A Pilot Study

Smirnova

Khamatnurova

Kharin

et al. 2022

Sensors

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The quality of modern measuring instruments has a strong influence on the speed of diagnosing diseases of the human musculoskeletal system. The research is focused on automatization of the method of gait analysis. The study involved six healthy subjects. The subjects walk straight. Each subject made several gait types: casual walking and imitation of a non-standard gait, including shuffling, lameness, clubfoot, walking from the heel, rolling from heel to toe, walking with hands in pockets, and catwalk. Each type of gait was recorded three times. For video fixation, the Vicon Nexus system was used. A total of 27 reflective markers were placed on the special anatomical regions. The goniometry methods were used. The walk data were divided by steps and by step phases. Kinematic parameters for estimation were formulated and calculated. An approach for data clusterization is presented. For this purpose, angle data were interpolated and the interpolation coefficients were used for clustering the data. The data were processed and four cluster groups were found. Typical angulograms for cluster groups were presented. For each group, average angles were calculated. A statistically significant difference was found between received cluster groups.

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“…A total of 13 infrared camera systems (VICON, Oxford Metrics Group, Oxford, UK, 100 Hz) recorded the 3D position of 65 reflective markers attached on anatomical landmarks of the different body segments (Plug-in Gait [38]) as well as the ground reaction forces recorded using force plate (AMTI, Watertown, MA, USA, 1000 Hz). Simultaneously, a 3D InCap system (MVN BIOMECH Awinda, Xsens Technologies, Enschede, The Netherlands, 60 Hz [39,40]), consisting of 17 IMUs, recorded the 3D body segment orientation after performing a previously developed functional calibration procedure [41]. Both systems were time synchronized based on the manufacturer's guidelines with a specific trigger at the start/stop recording time.…”

Section: Experimental Dataset Used To Develop and Validate The Incap ...mentioning

confidence: 99%

“…(1) The InCap validation dataset was used to calculate the joint kinematics following a previously developed functional calibration method-OpenIMUs [41]. (2) IMU-based kinematics were input to the probabilistic principal component analysis (PPCA) model to estimate the GRFM.…”

Section: Incap-based Workflow Overviewmentioning

confidence: 99%

Peak Tibiofemoral Contact Forces Estimated Using IMU-Based Approaches Are Not Significantly Different from Motion Capture-Based Estimations in Patients with Knee Osteoarthritis

Raimondo

Willems

Killen

et al. 2023

Sensors

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Altered tibiofemoral contact forces represent a risk factor for osteoarthritis onset and progression, making optimization of the knee force distribution a target of treatment strategies. Musculoskeletal model-based simulations are a state-of-the-art method to estimate joint contact forces, but they typically require laboratory-based input and skilled operators. To overcome these limitations, ambulatory methods, relying on inertial measurement units, have been proposed to estimated ground reaction forces and, consequently, knee contact forces out-of-the-lab. This study proposes the use of a full inertial-capture-based musculoskeletal modelling workflow with an underlying probabilistic principal component analysis model trained on 1787 gait cycles in patients with knee osteoarthritis. As validation, five patients with knee osteoarthritis were instrumented with 17 inertial measurement units and 76 opto-reflective markers. Participants performed multiple overground walking trials while motion and inertial capture methods were synchronously recorded. Moderate to strong correlations were found for the inertial capture-based knee contact forces compared to motion capture with root mean square error between 0.15 and 0.40 of body weight. The results show that our workflow can inform and potentially assist clinical practitioners to monitor knee joint loading in physical therapy sessions and eventually assess long-term therapeutic effects in a clinical context.

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Inertial Sensor-to-Segment Calibration for Accurate 3D Joint Angle Calculation for Use in OpenSim

Cited by 18 publications

References 81 publications

Design of Active Display Stand Combing the Pressure Sensor and Kinematics Algorithm

Design of Active Display Stand Combing the Pressure Sensor and Kinematics Algorithm

The Automatization of the Gait Analysis by the Vicon Video System: A Pilot Study

Peak Tibiofemoral Contact Forces Estimated Using IMU-Based Approaches Are Not Significantly Different from Motion Capture-Based Estimations in Patients with Knee Osteoarthritis

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