Implementing a Sensor Fusion Algorithm for 3D Orientation Detection with Inertial/Magnetic Sensors

Abyarjoo, Fatemeh; Barreto, Armando; Cofino, Jonathan; Ortega, Francisco R.

doi:10.1007/978-3-319-06773-5_41

Cited by 55 publications

(25 citation statements)

References 7 publications

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“…The results of the orientation estimation were not compared to a reference; however, the team studied the convergence of the measured quaternions. In addition, Abayarjoo et al used a similar IMU with a linear Kalman filter to determine the angle directly from the sensor, without passing through a quaternion analysis [23]. The proposed algorithm helped to overcome the limitations of the accelerometer, because accelerometers generally measure two components: an acceleration and a gravitational component.…”

Section: Introductionmentioning

confidence: 99%

A New Multi-Sensor Fusion Scheme to Improve the Accuracy of Knee Flexion Kinematics for Functional Rehabilitation Movements

Tannous

Istrate

Benlarbi-Delaï

et al. 2016

Sensors

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Exergames have been proposed as a potential tool to improve the current practice of musculoskeletal rehabilitation. Inertial or optical motion capture sensors are commonly used to track the subject’s movements. However, the use of these motion capture tools suffers from the lack of accuracy in estimating joint angles, which could lead to wrong data interpretation. In this study, we proposed a real time quaternion-based fusion scheme, based on the extended Kalman filter, between inertial and visual motion capture sensors, to improve the estimation accuracy of joint angles. The fusion outcome was compared to angles measured using a goniometer. The fusion output shows a better estimation, when compared to inertial measurement units and Kinect outputs. We noted a smaller error (3.96°) compared to the one obtained using inertial sensors (5.04°). The proposed multi-sensor fusion system is therefore accurate enough to be applied, in future works, to our serious game for musculoskeletal rehabilitation.

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Section: Introductionmentioning

confidence: 99%

A New Multi-Sensor Fusion Scheme to Improve the Accuracy of Knee Flexion Kinematics for Functional Rehabilitation Movements

Tannous

Istrate

Benlarbi-Delaï

et al. 2016

Sensors

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“…On considering the Accel_X, Accel_Y and Accel_Z as the accelerometer measurements (gravity acceleration) in the X, Y and Z, then equations (2) and (3) blow, would demonstrate how to calculate the angles Roll and Pitch [10]:…”

Section: A Absolute Orientationmentioning

confidence: 99%

Real-time monitoring of elderly using their connected walking stick

Lachtar¹,

Kachouri²,

Val³

2017

2017 International Conference on Smart, Monitored and Controlled Cities (SM2C)

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OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. Abstract-Lots of aging people rely on a caneasan assistive device to ovoid problems such as leg weakness and balance loss, which are presumed to haveinducedmanyfallincidents. In this paper, we present a new design and implementation of Canne3D system, a local monitoring system for elderly using their connected walking stick. Actually, the 3Dcane is modeled through consideration of real-time movements for a deep understanding of the person's state, including steps counting and calculating the distance traveled. We have applied a simple multi-stage thresholdingmethod based on the acceleration value. Experiments show that the algorithms appear to be robust in term of detection rate and false positive rate.

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“…The measurement process was performed using the Kinect TM sensor and 2 attached Shimmer TM sensors on the thigh and shank respectively, in order to measure the knee angle. In fact, five algorithms were tested: (1) 3D accelerometers [9], (2) Kalman filter between 3D accelerometers and gyroscopes [21], (3) Quaternion based extended Kalman filter using 3D accelerometers, gyroscopes and magnetometers [22], (4) Quaternion based Gradient Descent algorithm [23], and Quaternion based Kinect TM algorithm.…”

Section: B Evaluation Of Existing Orientation Measurementmentioning

confidence: 99%

Exploring various orientation measurement approaches applied to a serious game system for functional rehabilitation

Tannous

Istrate

Benlarbi-Delaï

et al. 2016

2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Abstract-Serious games have been established as a complementary tool for conventional rehabilitation. This trend proved to be beneficial for both experts and patients since the first are able to assign and monitor virtual reality games for their patients to be executed at home, and the latter are greatly motivated by the challenges of these games rather than the repeatable and boring rehabilitation movements. In a previous work, we proposed a serious game for lower limb rehabilitation of the musculoskeletal system using the Microsoft Kinect TM camera and a virtual environment. However, this system suffers from inaccurate kinematic measurement due to various external sources. Therefore, this paper explores various kinematic measurement technics to improve the accuracy of our system. Six real time orientation measurement algorithms were assessed and compared, using multiple types of sensors. The results obtained showed a better performance for our system. In fact, this study reinforced a clearer view on a low cost, real time portable system to be implemented at home.

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Implementing a Sensor Fusion Algorithm for 3D Orientation Detection with Inertial/Magnetic Sensors

Cited by 55 publications

References 7 publications

A New Multi-Sensor Fusion Scheme to Improve the Accuracy of Knee Flexion Kinematics for Functional Rehabilitation Movements

A New Multi-Sensor Fusion Scheme to Improve the Accuracy of Knee Flexion Kinematics for Functional Rehabilitation Movements

Real-time monitoring of elderly using their connected walking stick

Exploring various orientation measurement approaches applied to a serious game system for functional rehabilitation

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