A Wearable Automated System to Quantify Parkinsonian Symptoms Enabling Closed Loop Deep Brain Stimulation
Research output: Contribution to book/anthology/report/proceeding › Article in proceedings › Research › peer-review
DOI
- https://doi.org/10.1007/978-3-319-40379-3_2
Final published version
- Paolo Angeles, Imperial College London, London, UK. ,
- Michael Mace, Imperial College London, London, UK. ,
- Marcel Admiraal, Imperial College London, London, UK. ,
- Etienne Burdet, Imperial College London, London, UK. ,
- Nicola Pavese
- Ravi Vaidyanathan, Imperial College London, London, UK.
This study presents (1) the design and validation of a wearable sensor suite for the unobtrusive capture of heterogeneous signals indicative of the primary symptoms of Parkinson's disease; tremor, bradykinesia and muscle rigidity in upper extremity movement and (2) a model to characterise these signals as they relate to the symptom severity as addressed by the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS).
The sensor suite and detection algorithms managed to distinguish between the non-mimicked and mimicked MDS-UPDRS tests on healthy subjects (p
| Original language | English |
|---|---|
| Title of host publication | TOWARDS AUTONOMOUS ROBOTIC SYSTEMS, TAROS 2016 |
| Editors | L Alboul, D Damian, JM Aitken |
| Number of pages | 12 |
| Publisher | SPRINGER INT PUBLISHING AG |
| Publication year | 2016 |
| Pages | 8-19 |
| ISBN (print) | 978-3-319-40378-6 |
| DOIs | |
| Publication status | Published - 2016 |
| Externally published | Yes |
| Event | 17th Annual Conference on Towards Autonomous Robotic Systems (TAROS) - Sheffield Duration: 26 Jun 2016 → 1 Jul 2016 |
Conference
| Conference | 17th Annual Conference on Towards Autonomous Robotic Systems (TAROS) |
|---|---|
| By | Sheffield |
| Periode | 26/06/2016 → 01/07/2016 |
| Series | Lecture Notes in Artificial Intelligence |
|---|---|
| Volume | 9716 |
| ISSN | 0302-9743 |
- Parkinson's disease therapy device, Quantification of Parkinson's disease symptoms, Rigidity model, MONITORING-SYSTEM, LIMB BRADYKINESIA, DISEASE, QUANTIFICATION, RIGIDITY, TREMOR
Research areas
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ID: 112662878