Motor control is usually studied by having test subjects coming to the lab to participate in experiments, often using dedicated instruments and setups. While this approach remains the gold standard for scientific experimentation, it is also important to develop methods for remote monitoring. This is especially relevant for populations with reduced mobility or that cannot easily access health professional consultancy. Moreover, due to the current pandemic, such a need is even more urging. Here we obtained movement data from healthy participants (n=9) that were either at their homes or, as a control condition, were tested in the lab. To collect data we leveraged on the fact that a large fraction of the general population (60.8%) owns a smartphone, especially those between the ages of 18 and 49 (more than 90%). In addition, appropriate data logger applications (app) are freely available. As a proof of concept, we tested postural control, which was performed remotely at the homes of the participants during a videoconference. The experimenter instructed the participant to install a free available app (i.e., AndroSensor, Fiv Asim, for Android devices or Physics Toolbox Sensor Suite, Vieyra Software, for iPhones) on their smartphone, which allowed to record tri-axial accelerations (sampling frequency 100Hz). Following that, participants were instructed to strap their phone to the lower back and “stand quietly while barefooted for 80 seconds”. The experiment was performed in several conditions in a randomised order which included: eyes open vs closed, bipodalic vs monopodalic stance. A control condition, in which the smartphone was placed on the ground, was also included. In selected trials, a concurrent video-recording of the trials (extracted from the videoconference; a sound cue was used for synchronisation) was performed by the experimenter, to be used for off-line markerless tracking of kinematic data which were later compared with the app data. Preliminary results indicate that remote monitoring of motor performance is similar to that obtained in the lab, with the great advantage of being low cost, time-effective and scalable which is a step toward a location- independent investigation of motor control/performance parameters.
Remote monitoring of motor performance via smartphone applications and markerless tracking / E. QUARTA, G. VICHI, V. SORGENTE, R. BRAVI, E. J. COHEN, D. MINCIACCHI;. - ELETTRONICO. - (2021), pp. 0-0. (Intervento presentato al convegno SfN Global Connectome: A Virtual Event).
Remote monitoring of motor performance via smartphone applications and markerless tracking
E. QUARTA;V. SORGENTE;R. BRAVI;E. J. COHEN;D. MINCIACCHI
2021
Abstract
Motor control is usually studied by having test subjects coming to the lab to participate in experiments, often using dedicated instruments and setups. While this approach remains the gold standard for scientific experimentation, it is also important to develop methods for remote monitoring. This is especially relevant for populations with reduced mobility or that cannot easily access health professional consultancy. Moreover, due to the current pandemic, such a need is even more urging. Here we obtained movement data from healthy participants (n=9) that were either at their homes or, as a control condition, were tested in the lab. To collect data we leveraged on the fact that a large fraction of the general population (60.8%) owns a smartphone, especially those between the ages of 18 and 49 (more than 90%). In addition, appropriate data logger applications (app) are freely available. As a proof of concept, we tested postural control, which was performed remotely at the homes of the participants during a videoconference. The experimenter instructed the participant to install a free available app (i.e., AndroSensor, Fiv Asim, for Android devices or Physics Toolbox Sensor Suite, Vieyra Software, for iPhones) on their smartphone, which allowed to record tri-axial accelerations (sampling frequency 100Hz). Following that, participants were instructed to strap their phone to the lower back and “stand quietly while barefooted for 80 seconds”. The experiment was performed in several conditions in a randomised order which included: eyes open vs closed, bipodalic vs monopodalic stance. A control condition, in which the smartphone was placed on the ground, was also included. In selected trials, a concurrent video-recording of the trials (extracted from the videoconference; a sound cue was used for synchronisation) was performed by the experimenter, to be used for off-line markerless tracking of kinematic data which were later compared with the app data. Preliminary results indicate that remote monitoring of motor performance is similar to that obtained in the lab, with the great advantage of being low cost, time-effective and scalable which is a step toward a location- independent investigation of motor control/performance parameters.
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