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| Content Provider | ACM Digital Library |
|---|---|
| Author | Sarrafzadeh, Majid Nahapetian, Ani Lee, Sunghoon Ivan Woodbridge, Jonathan |
| Abstract | Due to the global trend of aging societies with increasing demand for low cost and high quality healthcare services, there has been extensive research and development directed toward wireless and remote healthcare technology that considers age-associated ailments. In this paper, we introduce Mobility Assessment and Remote Healthcare System (MARHS) that utilizes a force sensor in order to provide quantitative assessment of the mobility level of patients with movement disorder ailment, which is one common age-associated ailment. The proposed system also enables the remote healthcare services that allow patients to receive diagnoses from clinical experts without his/her presence. MARHS also contains a data analysis unit in order to provide information that summarizes the characteristics of symptoms of a group of patients (e.g., patients with a certain type of ailment) using a combination of feature ranking, feature selection, and classification algorithms. The results of the analyses on the data from a clinical trial show that the examination results of the proposed system can accurately recognize various groups of patients, such as, patients with (i) chronic obstructive pulmonary disease, (ii) hypertension, and (iii) cerebral vascular accident with an average accuracy of 90.05%, 82.60%, and 93.54%, respectively. |
| Starting Page | 333 |
| Ending Page | 342 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781450307819 |
| DOI | 10.1145/2110363.2110402 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2012-01-28 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Force sensors. Remote health Movement disorders |
| Content Type | Text |
| Resource Type | Article |
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