Publications (2)1.69 Total impact
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Article: Monitoring kinematic changes with fatigue in running using body-worn sensors.
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ABSTRACT: In this paper, we investigate monitoring of kinematic changes evoked by fatigue in running using wearable technology. Movement data were recorded with ETHOS devices. ETHOS is the ETH Orientation Sensor, a customized inertial measurement unit for unconstrained monitoring of human movement. We perform two real-world experiments, in which 21 runners of different skill levels participated. The real-world experiments capture two exhausting 45-min runs: one on a treadmill and one on a conventional outdoor track. We describe and evaluate algorithms to extract kinematic parameters from the sensor data. We identified parameters that change with fatigue for all runners, ones that change for runners of distinct skill levels, and ones that are dependent on an individual's running technique. Overall, we found that observations from treadmill running are not always generalizable to outdoor running. We, thus, argue for using wearable technology to provide athletes and trainers with continuous, quantitative objective measurements of running technique. These could be used to further gain insight into the complex relationship of running kinematics, injury risk, fatigue, and running economy.IEEE transactions on information technology in biomedicine: a publication of the IEEE Engineering in Medicine and Biology Society 06/2012; 16(5):983-90. · 1.69 Impact Factor -
Conference Proceeding: ETHOS: Miniature orientation sensor for wearable human motion analysis
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ABSTRACT: Inertial and magnetic sensors offers a sourceless and mobile option to obtain body posture and motion for personal sports or healthcare assistants, if sensors could be unobtrusively integrated in casual garments and accessories. We present in this paper design, implementation, and evaluation results for a novel miniature attitude and heading reference system (AHRS) named ETHOS using current off-the-shelf technologies. ETHOS has a unit size of 2.5 cm<sup>3</sup>, which is substantially below most currently marketed attitude heading reference systems, while the unit contains processing resources to estimate its orientation online. Results on power consumption in relation to sampling frequency and sensor use are presented. Moreover two sensor fusion algorithms to estimate orientation: a quaternion based Kalman-, and a complementary filter. Evaluations of orientation estimation accuracy in static and dynamic conditions revealed that complementary filtering reached sufficient accuracy while consuming 46% of a Kalman's power. The system runtime of ETHOS was found to be 10 hours at a complementary filter update rate of 128Hz. Furthermore, we found that a ETHOS prototype functioned with a sufficient accuracy in estimating hu man movement in real-life conditions using an arm rehabilitation robot.Sensors, 2010 IEEE; 12/2010
