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      The Use of Accelerometers and Gyroscopes to Estimate Hip and Knee Angles on Gait Analysis

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          Abstract

          In this paper the performance of a sensor system, which has been developed to estimate hip and knee angles and the beginning of the gait phase, have been investigated. The sensor system consists of accelerometers and gyroscopes. A new algorithm was developed in order to avoid the error accumulation due to the gyroscopes drift and vibrations due to the ground contact at the beginning of the stance phase. The proposed algorithm have been tested and compared to some existing algorithms on over-ground walking trials with a commercial device for assisted gait. The results have shown the good accuracy of the angles estimation, also in high angle rate movement.

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          Estimation of IMU and MARG orientation using a gradient descent algorithm.

          Sebastian O H Madgwick, Andrew Vaidyanathan, Rhett Harrison (2010)
          This paper presents a novel orientation algorithm designed to support a computationally efficient, wearable inertial human motion tracking system for rehabilitation applications. It is applicable to inertial measurement units (IMUs) consisting of tri-axis gyroscopes and accelerometers, and magnetic angular rate and gravity (MARG) sensor arrays that also include tri-axis magnetometers. The MARG implementation incorporates magnetic distortion compensation. The algorithm uses a quaternion representation, allowing accelerometer and magnetometer data to be used in an analytically derived and optimised gradient descent algorithm to compute the direction of the gyroscope measurement error as a quaternion derivative. Performance has been evaluated empirically using a commercially available orientation sensor and reference measurements of orientation obtained using an optical measurement system. Performance was also benchmarked against the propriety Kalman-based algorithm of orientation sensor. Results indicate the algorithm achieves levels of accuracy matching that of the Kalman based algorithm; < 0.8° static RMS error, < 1.7° dynamic RMS error. The implications of the low computational load and ability to operate at small sampling rates significantly reduces the hardware and power necessary for wearable inertial movement tracking, enabling the creation of lightweight, inexpensive systems capable of functioning for extended periods of time. © 2011 IEEE
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            A practical gait analysis system using gyroscopes.

            Kaiyu Tong, Malcolm Granat (1999)
            This study investigated the possibility of using uni-axial gyroscopes to develop a simple portable gait analysis system. Gyroscopes were attached on the skin surface of the shank and thigh segments and the angular velocity for each segment was recorded in each segment. Segment inclinations and knee angle were derived from segment angular velocities. The angular signals from a motion analysis system were used to evaluate the angular velocities and the derived signals from the gyroscopes. There was a good correlation between these signals. When performing a turn the signals of segment inclination and knee angle drifted. Two methods were used to solve this: automatically resetting the system to re-initialise the angle in each gait cycle, and high-pass filtering. They both successfully corrected this drift. A single gyroscope on the shank segment could provide information on segment inclination range, cadence, number of steps, and an estimation of stride length and walking speed.
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              Three Dimensional Gait Analysis Using Wearable Acceleration and Gyro Sensors Based on Quaternion Calculations

              Shigeru Tadano, Ryo Takeda, Hiroaki Miyagawa (2013)
              This paper proposes a method for three dimensional gait analysis using wearable sensors and quaternion calculations. Seven sensor units consisting of a tri-axial acceleration and gyro sensors, were fixed to the lower limbs. The acceleration and angular velocity data of each sensor unit were measured during level walking. The initial orientations of the sensor units were estimated using acceleration data during upright standing position and the angular displacements were estimated afterwards using angular velocity data during gait. Here, an algorithm based on quaternion calculation was implemented for orientation estimation of the sensor units. The orientations of the sensor units were converted to the orientations of the body segments by a rotation matrix obtained from a calibration trial. Body segment orientations were then used for constructing a three dimensional wire frame animation of the volunteers during the gait. Gait analysis was conducted on five volunteers, and results were compared with those from a camera-based motion analysis system. Comparisons were made for the joint trajectory in the horizontal and sagittal plane. The average RMSE and correlation coefficient (CC) were 10.14 deg and 0.98, 7.88 deg and 0.97, 9.75 deg and 0.78 for the hip, knee and ankle flexion angles, respectively.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Sensors (Basel)
                Journal ID (iso-abbrev): Sensors (Basel)
                Title: Sensors (Basel, Switzerland)
                Publisher: Molecular Diversity Preservation International (MDPI)
                ISSN (Electronic): 1424-8220
                Publication date Collection: May 2014
                Publication date (Electronic): 13 May 2014
                Volume: 14
                Issue: 5
                Pages: 8430-8446
                Affiliations
                Dipartimento di Energia, Ingegneria dell'Informazione, e Modelli Matematici (DEIM), University of Palermo, Viale delle Scienze, Palermo, Italy; E-Mails: francesco.alonge@ 123456unipa.it (F.A.); elisa.cucco@ 123456unipa.it (E.C.); pulizzotto.alessio@ 123456gmail.com (A.P.)
                Author notes

                Authors Contribution: All the authors conceived of and designed the study. In particular, Filippo D'Ippolito, Elisa Cucco and Francesco Alonge have conceived of the APB method; Alessio Pulizzotto has conceived of the ICF method and realized the experimental setup. All authors read and approved the manuscript.

                [* ] Author to whom correspondence should be addressed; E-Mail: filippo.dippolito@ 123456unipa.it ; Tel.: +39-91-2386-3606; Fax: +39-91-427-940.
                Article
                Publisher ID: sensors-14-08430
                DOI: 10.3390/s140508430
                PMC ID: 4063036
                PubMed ID: 24828578
                SO-VID: 702291a1-9318-42d6-8c69-18bcafb80a14
                Copyright © © 2014 by the authors; licensee MDPI, Basel, Switzerland.
                License:

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license ( http://creativecommons.org/licenses/by/3.0/).

                History
                Date received : 14 February 2014
                Date revision received : 29 March 2014
                Date accepted : 07 May 2014
                Categories
                Subject: Article

                ScienceOpen disciplines: Biomedical engineering
                Keywords: gait analysis,joint angles estimation,inertial sensors
                Data availability:
                ScienceOpen disciplines: Biomedical engineering
                Keywords: gait analysis, joint angles estimation, inertial sensors

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