Name
Title | ||
|---|---|---|
Classifying persons with dementia from control subjects when ascending and descending stairs based on a single pelvis-mounted sensor |
Abstract | ||
|---|---|---|
As part of a larger program of work to understand how people with dementia navigate their environment and use visual cues we present data which uses a single sensor - an IMU placed on the pelvis - to classify people into two groups on the basis of hesitancy when ascending/descending stairs: individuals with dementia vs age-matched controls. The classification was conducted on data collected from 34 people (14 controls; 20 people with dementia, comprising 10 with typical Alzheimeru0027s disease [tAD] and 10 with posterior cortical atrophy [PCA]) walking up a set of 4 steps. Attributes used to discriminate those with and without dementia were the mean and root mean square values of: resultant acceleration, roll, pitch and yaw. Each personu0027s data was allocated to one of two datasets (N=17, N=17). A weighted nearest neighbor classifier was trained on each dataset in turn and subsequently used on the remaining dataset. Overall accuracy of the classifier was 0.67, with a precision of 0.62 and recall of 0.47. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.4108/eai.16-5-2016.2263971 | international conference on pervasive computing |
Field | DocType | Citations |
Computer science,Computer network,Inertial measurement unit,Artificial intelligence,Physical medicine and rehabilitation,Classifier (linguistics),Stairs,Sensory cue,Posterior cortical atrophy,Recall,Pelvis,Machine learning,Dementia | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 9 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Catherine Holloway | 1 | 4 | 6.34 |
| Ian McCarthy | 2 | 0 | 0.68 |
| Tatsuto Suzuki | 3 | 1 | 1.18 |
| Keir X. Yong | 4 | 1 | 1.16 |
| Biao Yang | 5 | 0 | 1.01 |
| Amelia M. Carton | 6 | 0 | 0.34 |
| Nadia Bianchi-Berthouze | 7 | 1239 | 98.61 |
| Nick Tyler | 8 | 16 | 1.07 |
| Sebastian J. Crutch | 9 | 6 | 3.01 |