A smart pen prototype with adaptive algorithms for stabilizing handwriting tremor signals in Parkinson’s disease
Abstract This study presents a smart pen prototype designed to dynamically mitigate hand tremors, thereby enhancing writing quality and user comfort for individuals with conditions such as Parkinson’s disease. The device employs an accelerometer for real-time tremor detection, a microcontroller for...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-14196-5 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849763813679693824 |
|---|---|
| author | Jéssica Cristina Tironi Anita Fernandes Renata Coelho Borges Luis Augusto Silva Wemerson Delcio Parreira |
| author_facet | Jéssica Cristina Tironi Anita Fernandes Renata Coelho Borges Luis Augusto Silva Wemerson Delcio Parreira |
| author_sort | Jéssica Cristina Tironi |
| collection | DOAJ |
| description | Abstract This study presents a smart pen prototype designed to dynamically mitigate hand tremors, thereby enhancing writing quality and user comfort for individuals with conditions such as Parkinson’s disease. The device employs an accelerometer for real-time tremor detection, a microcontroller for rapid data processing, and a vibration motor to counteract tremor effects. Adaptive algorithms—including Fx-LMS, Fx-NLMS, a combined Fx-LMS/NLMS approach, RLS, and the Kalman Filter—were evaluated using signals from the NewHandPD dataset. Simulation results revealed that although the RLS algorithm achieved the lowest mean square error, the Kalman Filter converged approximately eight times faster, a finding that was confirmed through microcontroller tests and further validated on an orbital shaking table under constant and variable tremor conditions. These outcomes underscore the potential of the Kalman Filter as a non-invasive, adaptive solution for real-time tremor mitigation in assistive writing devices. Future improvements may include integrating additional sensors and further optimizing microcontroller performance to enhance overall adaptability and accuracy. |
| format | Article |
| id | doaj-art-6ba73bb2d3d24263a5888fa51c57232c |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-6ba73bb2d3d24263a5888fa51c57232c2025-08-20T03:05:18ZengNature PortfolioScientific Reports2045-23222025-08-0115111110.1038/s41598-025-14196-5A smart pen prototype with adaptive algorithms for stabilizing handwriting tremor signals in Parkinson’s diseaseJéssica Cristina Tironi0Anita Fernandes1Renata Coelho Borges2Luis Augusto Silva3Wemerson Delcio Parreira4Polytechnic School, University of Vale do Itajaí (UNIVALI)Polytechnic School, University of Vale do Itajaí (UNIVALI)Graduate Program in Biomedical Engineering (PPGEB), Federal University of Technology – Paraná (UTFPR)Department of Computer Science, Faculty of Science, Universidad de SalamancaFaculty of Electrical Engineering, Polytechnic School, Pontifical Catholic University of Campinas (PUC-Campinas)Abstract This study presents a smart pen prototype designed to dynamically mitigate hand tremors, thereby enhancing writing quality and user comfort for individuals with conditions such as Parkinson’s disease. The device employs an accelerometer for real-time tremor detection, a microcontroller for rapid data processing, and a vibration motor to counteract tremor effects. Adaptive algorithms—including Fx-LMS, Fx-NLMS, a combined Fx-LMS/NLMS approach, RLS, and the Kalman Filter—were evaluated using signals from the NewHandPD dataset. Simulation results revealed that although the RLS algorithm achieved the lowest mean square error, the Kalman Filter converged approximately eight times faster, a finding that was confirmed through microcontroller tests and further validated on an orbital shaking table under constant and variable tremor conditions. These outcomes underscore the potential of the Kalman Filter as a non-invasive, adaptive solution for real-time tremor mitigation in assistive writing devices. Future improvements may include integrating additional sensors and further optimizing microcontroller performance to enhance overall adaptability and accuracy.https://doi.org/10.1038/s41598-025-14196-5Kalman FiltersParkinson’s diseasePen prototypeTremor mitigationAdaptive control |
| spellingShingle | Jéssica Cristina Tironi Anita Fernandes Renata Coelho Borges Luis Augusto Silva Wemerson Delcio Parreira A smart pen prototype with adaptive algorithms for stabilizing handwriting tremor signals in Parkinson’s disease Scientific Reports Kalman Filters Parkinson’s disease Pen prototype Tremor mitigation Adaptive control |
| title | A smart pen prototype with adaptive algorithms for stabilizing handwriting tremor signals in Parkinson’s disease |
| title_full | A smart pen prototype with adaptive algorithms for stabilizing handwriting tremor signals in Parkinson’s disease |
| title_fullStr | A smart pen prototype with adaptive algorithms for stabilizing handwriting tremor signals in Parkinson’s disease |
| title_full_unstemmed | A smart pen prototype with adaptive algorithms for stabilizing handwriting tremor signals in Parkinson’s disease |
| title_short | A smart pen prototype with adaptive algorithms for stabilizing handwriting tremor signals in Parkinson’s disease |
| title_sort | smart pen prototype with adaptive algorithms for stabilizing handwriting tremor signals in parkinson s disease |
| topic | Kalman Filters Parkinson’s disease Pen prototype Tremor mitigation Adaptive control |
| url | https://doi.org/10.1038/s41598-025-14196-5 |
| work_keys_str_mv | AT jessicacristinatironi asmartpenprototypewithadaptivealgorithmsforstabilizinghandwritingtremorsignalsinparkinsonsdisease AT anitafernandes asmartpenprototypewithadaptivealgorithmsforstabilizinghandwritingtremorsignalsinparkinsonsdisease AT renatacoelhoborges asmartpenprototypewithadaptivealgorithmsforstabilizinghandwritingtremorsignalsinparkinsonsdisease AT luisaugustosilva asmartpenprototypewithadaptivealgorithmsforstabilizinghandwritingtremorsignalsinparkinsonsdisease AT wemersondelcioparreira asmartpenprototypewithadaptivealgorithmsforstabilizinghandwritingtremorsignalsinparkinsonsdisease AT jessicacristinatironi smartpenprototypewithadaptivealgorithmsforstabilizinghandwritingtremorsignalsinparkinsonsdisease AT anitafernandes smartpenprototypewithadaptivealgorithmsforstabilizinghandwritingtremorsignalsinparkinsonsdisease AT renatacoelhoborges smartpenprototypewithadaptivealgorithmsforstabilizinghandwritingtremorsignalsinparkinsonsdisease AT luisaugustosilva smartpenprototypewithadaptivealgorithmsforstabilizinghandwritingtremorsignalsinparkinsonsdisease AT wemersondelcioparreira smartpenprototypewithadaptivealgorithmsforstabilizinghandwritingtremorsignalsinparkinsonsdisease |