Abstract (may include machine translation)
A software tool has been developed to support the objective diagnosis of patients with Parkinson's Disease (PD). Patients completed hand exercises using a personal computer mouse and data has been gathered for further studies. We have analyzed different parameters and suggest using a particular parameter vector containing median and standard deviation values for tracking the daily changes in PD patients' status. Using the classification abilities of self-organizing feature maps (SOFM) we were able to provide support for the diagnostic process.
Original language | English |
---|---|
Pages (from-to) | 3190-3193 |
Number of pages | 4 |
Journal | Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings |
Volume | 26 |
DOIs | |
State | Published - 2004 |
Externally published | Yes |
Event | Conference Proceedings - 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2004 - San Francisco, CA, United States Duration: 1 Sep 2004 → 5 Sep 2004 |
Keywords
- Neural network
- Objective diagnosis
- Parkinson's Disease
- Self-organizing map