TY - GEN
T1 - Inertial sensor based gait analysis discriminates subjects with and without visual impairment caused by simulated macular degeneration
AU - Kanzler, Christoph M.
AU - Barth, Jens
AU - Klucken, Jochen
AU - Eskofier, Bjoern M.
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/10/13
Y1 - 2016/10/13
N2 - Macular degeneration is the third leading cause of blindness worldwide and the leading cause of blindness in the developing world. The analysis of gait parameters can be used to assess the influence of macular degeneration on gait. This study examines the effect of macular degeneration on gait using inertial sensor based 3D spatio-temporal gait parameters. We acquired gait data from 21 young and healthy subjects during a 40 m obstacle walk. All subjects had to perform the gait trial with and without macular degeneration simulation glasses. The order of starting with or without glasses alternated between each subject in order to test for training effects. Multiple 3D spatio-temporal gait parameters were calculated for the normal vision as well as the impaired vision groups. The parameters trial time, stride time, stride time coefficient of variation (CV), stance time, stance time CV, stride length, cadence, gait velocity and angle at toe off showed statistically significant differences between the two groups. Training effects were visible for the trials which started without vision impairment. Inter-group differences in the gait pattern occurred due to an increased sense of insecurity related with the loss of visual acuity from the simulation glasses. In summary, we showed that 3D spatio-temporal gait parameters derived from inertial sensor data are viable to detect differences in the gait pattern of subjects with and without a macular degeneration simulation. We believe that this study provides the basis for an in-depth analysis regarding the impact of macular degeneration on gait.
AB - Macular degeneration is the third leading cause of blindness worldwide and the leading cause of blindness in the developing world. The analysis of gait parameters can be used to assess the influence of macular degeneration on gait. This study examines the effect of macular degeneration on gait using inertial sensor based 3D spatio-temporal gait parameters. We acquired gait data from 21 young and healthy subjects during a 40 m obstacle walk. All subjects had to perform the gait trial with and without macular degeneration simulation glasses. The order of starting with or without glasses alternated between each subject in order to test for training effects. Multiple 3D spatio-temporal gait parameters were calculated for the normal vision as well as the impaired vision groups. The parameters trial time, stride time, stride time coefficient of variation (CV), stance time, stance time CV, stride length, cadence, gait velocity and angle at toe off showed statistically significant differences between the two groups. Training effects were visible for the trials which started without vision impairment. Inter-group differences in the gait pattern occurred due to an increased sense of insecurity related with the loss of visual acuity from the simulation glasses. In summary, we showed that 3D spatio-temporal gait parameters derived from inertial sensor data are viable to detect differences in the gait pattern of subjects with and without a macular degeneration simulation. We believe that this study provides the basis for an in-depth analysis regarding the impact of macular degeneration on gait.
UR - http://www.scopus.com/inward/record.url?scp=85009133558&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2016.7591845
DO - 10.1109/EMBC.2016.7591845
M3 - Conference contribution
C2 - 28269386
AN - SCOPUS:85009133558
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 4979
EP - 4982
BT - 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
Y2 - 16 August 2016 through 20 August 2016
ER -