Classification of normal gait from pathological gait as then can be used as indicator of falling among subjects requires the correct choice of sensor location in the insole. Such a flexi force- sensor can be used unde...Classification of normal gait from pathological gait as then can be used as indicator of falling among subjects requires the correct choice of sensor location in the insole. Such a flexi force- sensor can be used underneath foot to measure vertical ground reaction force. To start with, the most relevant information (parameters) that can characterize the recorded signals are extracted from the vertical ground reaction force signals. Then Receiver Operating Characteristic curve is used to evaluate the features upon 8 sensors underneath each foot located at different locations. To confirm results obtained, features are passed upon a chosen classifier, in this paper K-nearest neighbors algorithm is chosen. Results show that the sensor located at the inner arch of the sole of the foot (i.e. at the mid foot) holds the most relevant information needed for better classification compared to other sensors.展开更多
In this paper, a comparative analysis of walking patterns during different cognitive states is conducted, followed by the classification of our database into Fallers and Non-fallers;by Fallers we describe subjects wit...In this paper, a comparative analysis of walking patterns during different cognitive states is conducted, followed by the classification of our database into Fallers and Non-fallers;by Fallers we describe subjects with repeated falling history. Vertical Ground Reaction Forces (VGRF) acquired from underneath the heel and toes of both feet are processed and analyzed for that endeavor. The subjects underwent three levels of tasks: 1) Single task: Walking at self-selected-speed (MS), 2) Dual task: Walking while performing a verbal fluency task (MF) and 3) Complex Dual task: Walking while counting backwards (MD).The ultimate objective of our research is fall prediction among the elderly by characterizing the variation of time-domain feature of Gait signals. For that, walking VGRF is analyzed and tested for the existence of indicators of the effect of dual task on subject falling susceptibility, whether parametric or pattern-wise analysis. As a result to our work, dual task in Fallers VGRF signals were recognized at 74% while at those non-fallers were recognized at 85%. Most importantly, subjects with history of fall have shown more potential to change the way they walk while performing mathematical cognitive task.展开更多
文摘Classification of normal gait from pathological gait as then can be used as indicator of falling among subjects requires the correct choice of sensor location in the insole. Such a flexi force- sensor can be used underneath foot to measure vertical ground reaction force. To start with, the most relevant information (parameters) that can characterize the recorded signals are extracted from the vertical ground reaction force signals. Then Receiver Operating Characteristic curve is used to evaluate the features upon 8 sensors underneath each foot located at different locations. To confirm results obtained, features are passed upon a chosen classifier, in this paper K-nearest neighbors algorithm is chosen. Results show that the sensor located at the inner arch of the sole of the foot (i.e. at the mid foot) holds the most relevant information needed for better classification compared to other sensors.
文摘In this paper, a comparative analysis of walking patterns during different cognitive states is conducted, followed by the classification of our database into Fallers and Non-fallers;by Fallers we describe subjects with repeated falling history. Vertical Ground Reaction Forces (VGRF) acquired from underneath the heel and toes of both feet are processed and analyzed for that endeavor. The subjects underwent three levels of tasks: 1) Single task: Walking at self-selected-speed (MS), 2) Dual task: Walking while performing a verbal fluency task (MF) and 3) Complex Dual task: Walking while counting backwards (MD).The ultimate objective of our research is fall prediction among the elderly by characterizing the variation of time-domain feature of Gait signals. For that, walking VGRF is analyzed and tested for the existence of indicators of the effect of dual task on subject falling susceptibility, whether parametric or pattern-wise analysis. As a result to our work, dual task in Fallers VGRF signals were recognized at 74% while at those non-fallers were recognized at 85%. Most importantly, subjects with history of fall have shown more potential to change the way they walk while performing mathematical cognitive task.
