Over the years, smartphones have become tools for scientific and clinical research. They can, for instance, be used to assess range of motion and joint angle measurement. In this paper, our aim was to determine if smartphones are reliable and accurate enough for clinical motion research. This work proposes an evaluation of different smartphone sensors performance and different manufacturer algorithm performances with the comparison to the gold standard, an industrial robotic arm with an actual standard use inertial motion unit in clinical measurement, an Xsens product. Both dynamic and static protocols were used to perform these comparisons. Root Mean Square (RMS) mean values results for static protocol are under 0.3° for the different smartphones. RMS mean values results for dynamic protocol are more prone to bias induced by Euler angle representation. Statistical results prove that there are no filter effect on results for both protocols and no hardware effect. Smartphones performance can be compared to the Xsens gold standard for clinical research.
This article proposes an implementation of a Kalman Filter, using inertial sensors of a Smartphone, to estimate 3D angulation of the trunk. The developped system monitors the trunk angular evolution during bipedal stance and helps the user to improve balance through a configurable and integrated auditory-biofeedback loop. A proof-of-concept study was performed to assess the effectiveness of this so-called iBalance-ABF -smartphone-based audio-biofeedback system -in improving balance during bipedal standing. Results showed that young healthy individuals were able to efficiently use ABF on sagittal trunk tilt to improve their balance in the ML direction. These findings suggest that iBalance-ABF system as a Telerehabilitation system which could represent a suitable solution for Ambient Assisted Living technologies.
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