TY - GEN
T1 - Accurate gait analysis in post-stroke patients using a single inertial measurement unit
AU - Parisi, Federico
AU - Ferrari, Gianluigi
AU - Baricich, Alessio
AU - D'Innocenzo, Marco
AU - Cisari, Carlo
AU - Mauro, Alessandro
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/7/18
Y1 - 2016/7/18
N2 - Improving independent mobility in post-stroke patients is one of the main goals of most rehabilitation strategies. While quantitative gait assessment is crucial to provide a meaningful feedback on the recovery progress, the irregularity of hemiparetic walking prevents the use of classical Inertial Measurement Unit (IMU)-based gait analysis algorithms. In this paper, we propose a novel low-cost system, which relies on a single wearable IMU attached to the lower trunk, to estimate spatio-temporal gait parameters of both hemiparetic and healthy subjects. A new procedure for temporal features' computation and two modified versions of well-known step length (i.e., spatial features) estimators are derived. In both cases, we exploit dynamic calibration constants, related to the power of an individual gait pattern, to deal with the typical asymmetry and inter-subject variability of hemiparetic gait. The spatio-temporal features estimated with the proposed methods are compared with ground-truth parameters extracted by an optoelectronic system. The obtained results show very high correlations between estimated and reference values.
AB - Improving independent mobility in post-stroke patients is one of the main goals of most rehabilitation strategies. While quantitative gait assessment is crucial to provide a meaningful feedback on the recovery progress, the irregularity of hemiparetic walking prevents the use of classical Inertial Measurement Unit (IMU)-based gait analysis algorithms. In this paper, we propose a novel low-cost system, which relies on a single wearable IMU attached to the lower trunk, to estimate spatio-temporal gait parameters of both hemiparetic and healthy subjects. A new procedure for temporal features' computation and two modified versions of well-known step length (i.e., spatial features) estimators are derived. In both cases, we exploit dynamic calibration constants, related to the power of an individual gait pattern, to deal with the typical asymmetry and inter-subject variability of hemiparetic gait. The spatio-temporal features estimated with the proposed methods are compared with ground-truth parameters extracted by an optoelectronic system. The obtained results show very high correlations between estimated and reference values.
UR - http://www.scopus.com/inward/record.url?scp=84983419749&partnerID=8YFLogxK
U2 - 10.1109/BSN.2016.7516284
DO - 10.1109/BSN.2016.7516284
M3 - Conference contribution
AN - SCOPUS:84983419749
T3 - BSN 2016 - 13th Annual Body Sensor Networks Conference
SP - 335
EP - 340
BT - BSN 2016 - 13th Annual Body Sensor Networks Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th Annual Body Sensor Networks Conference, BSN 2016
Y2 - 14 June 2016 through 17 June 2016
ER -