STABILIT: Adaptive Non-Invasive Neuromodulation for Tremor Suppression

Aging populations are increasingly susceptible to neurological and movement-related disorders, placing growing pressure on healthcare systems and long-term patient care. Tremors are a common movement disorder caused by damage in specific regions of the brain and are often associated with neurological disorders linked to aging.

My project was inspired by seeing firsthand how tremors interfere with confidence, motor control, and independence. I saw how Parkinson’s disease can make tasks like eating, writing, buttoning clothes, and even holding a cup difficult.

I realized that many current approaches rely on medication, invasive procedures, or tools that do not adapt to the user’s changing neurological state. Tremor severity can fluctuate due to stress, fatigue, movement intention, and other factors, reducing long-term effectiveness.

This project builds on my 2023 Canada-Wide Science Fair project, TM&R Band: Age with Confidence, which investigated whether a wrist worn device could monitor and reduce tremors. That project used motion sensing in the arms and motor trials to determine severity/reduction of the tremor.

The current project, StabiliT, continues from that prior work but expands it into a neuromodulation system. StabiliT adds neural monitoring (EEG), a rebuilt IMU system, a decision engine, stimulation control, non invasive cervical/vagus nerve stimulation, and adjustment of stimulation intensity based on feedback. The project also includes a trial run with the following sections: rest tremor, finger tapping, line drawing, spiral drawing, and spoon-feeding style movement tasks to determine tremor severity/reduction. (Awan, 2023)

The system works in real time, adjusting stimulation intensity in real time. There are six stages that respond to tremor activity:

Motion Detection: A wrist-worn inertial measurement unit (IMU) captures hand movement, this data provides a direct measurement of the physical instability.

Neural Monitoring: Electrodes are placed over the motor cortex picking up activity associated with movement control.

Decision Engine: Features from above (Motion & Neural activity) are fed into the microcontroller to classify the tremor state (stable, voluntary, tremor) and determines if intervention is required by the stimulation unit, the settings and intensity of the stimulation unit is set based on this activity.

Relay Control Interface: Signals are sent from the decision engine to a set of relays that act as a switch, each controlling a button on the stimulation unit. Each relay operates in an activation sequence, increasing/decreasing intensity by increments. Step values are used to represent the number of relay triggered button clicks which are used to adjust intensity.

Each signal to the relay is time controlled (about 80-200 ms) to emulate a physical button press.

A value of +1 corresponds to a single relay activation (one step increase)

A value of -3 corresponds to three relay activations (3 step decrease)

Neural activity was recorded during motor-control activity to evaluate stability and adaptive stimulation response. EEG activity was synchronized with IMU motion data to analyze if stimulation intensity affected movement.

These motor assessment tasks build on the testing structure used in my 2023 TM&R Band project. (Awan, 2023)

The main work completed since the 2023 project includes:

1. Integrating EEG for data collection and monitoring.

2. Rebuilding the wrist-worn IMU system to measure motor activity in real time.

3. Developing a pipeline that uses motion detection, neural monitoring, a decision engine, neuromodulation output, and feedback adjustment.

4. Changing the stimulation approach from a wrist-based unit to non-invasive cervical/vagus nerve stimulation.

5. Creating an interface to adjust stimulation settings by simulating timed button presses on the stimulation unit.

6. Synchronizing EEG activity with IMU motion data to evaluate motor activity and adaptive stimulation effectiveness.

7. Completing an analysis showing an approximate 9–12.4% reduction in tremor amplitude following stimulation.

8. Developing an interface for the user to view improvement over time.

The next part of this project is to test with more subjects.

Future work will include:

Expand EEG-assisted adaptive stimulation validation across broader participant groups

Investigate machine learning based state prediction using neural data

Work on the system to be reduced into a fully wearable form factor with improved electrode design and safety features

REFERENCES

Aetna International. (2023). The ageing population: Exploring the impact on healthcare systems and economies. Retrieved from https://www.aetnainternational.com/en/about-us/explore/future-health/ageing-population-graphics.html

American Academy of Family Physicians. (2003). Differentiation and diagnosis of tremor. Retrieved from https://www.aafp.org/afp/2003/0115/p381.html

Awan, Shayan. “TM&R Band: Age with Confidence.” ProjectBoard, Youth Science Canada, 2023, https://partner.projectboard.world/ysc/project/tmandr-band-age-with-confidence.

Berrios Santiago, E. A. (2019). Retrieved from https://prcrepository.org/item/5cfe21821dabf625fe7e00c8

Calatrio, G., Deuschl, G., & Wierzbicka, M. (2021). Mechanisms of action of deep brain stimulation for essential tremor. Movement Disorders Clinical Practice, 8(8), 1053–1059. https://doi.org/10.1002/mdc3.13310

Cleveland Clinic. (n.d.). Tremor. Retrieved from https://my.clevelandclinic.org/health/diseases/15245-tremor

Detection. (n.d.). Retrieved from https://link.springer.com/article/10.1007/s42242-022-00199-y/tables/2

GeeksforGeeks. (n.d.). How to change legend font size in Matplotlib? Retrieved from https://www.geeksforgeeks.org/how-to-change-legend-font-size-in-matplotlib/

Henderson, E. J., Lord, S. R., Close, J. C. T., & Whelan, B. M. (2021). Older people and COVID-19: Isolation, risk and ageism. Australasian Journal on Ageing, 40(2), 129–133. https://doi.org/10.1111/ajag.12859

Hermanowicz, N., Edwards, K., & Lackner, R. (2016). Treatment of essential tremor with transcranial magnetic resonance-guided focused ultrasound surgery. Tremor and Other Hyperkinetic Movements, 6, 376. https://doi.org/10.7916/D87M0Z6V

Islam, M. R., Ahamed, S. I., & Hossain, M. S. (2016). A continuous hand gestures recognition technique for human-machine interaction using accelerometer and gyroscope sensors. International Journal of Distributed Sensor Networks, 12(3), 1–12. https://doi.org/10.1155/2016/3038359

Kantarci, K., Petersen, R. C., Boeve, B. F., Knopman, D. S., Weigand, S. D., O'Brien, P. C., et al. (2022). Association of Alzheimer disease neuropathologic changes with brain atrophy and cognition in older adults without dementia. Age and Ageing, 51(7), 1089–1094. https://doi.org/10.1093/ageing/afac135

Khan Academy. (n.d.). Acceleration. Retrieved from https://www.khanacademy.org/science/physics/one-dimensional-motion/acceleration-tutorial/a/acceleration-article

Mayo Clinic. (n.d.). Tremors: Symptoms & causes. Retrieved from https://www.mayoclinic.org/diseases-conditions/tremors/symptoms-causes/syc-20351625

OpenAI. (2023). ChatGPT (Mar 14 version) [Large language model]. https://chat.openai.com/chat

MedlinePlus. (2023). Tremor. Retrieved from https://medlineplus.gov/tremor.html

Medscape. (n.d.). Tremor: Pathophysiology, classification, and diagnosis. Retrieved from https://emedicine.medscape.com/article/1150290-overview

National Institute of Neurological Disorders and Stroke. (n.d.). Tremor: Hope through research. Retrieved from https://www.ninds.nih.gov/health-information/disorders/tremor

National Institute of Neurological Disorders and Stroke. (n.d.). Deep brain stimulation for Parkinson's disease. Retrieved from https://www.ninds.nih.gov/Disorders/Patient-Caregiver-Education/Fact-Sheets/Deep-Brain-Stimulation-Parkinsons-Disease

OpenAI. (2023). ChatGPT (Mar 14 version) [Large language model]. https://chat.openai.com/chat

Parkinson’s Foundation. (n.d.). Tremor. Retrieved from https://www.parkinson.org/Understanding-Parkinsons/Symptoms/Movement-Symptoms/Tremor

ResearchGate. (2022). Differential diagnosis of common types of tremor. Retrieved from https://www.researchgate.net/figure/Differential-diagnosis-of-common-types-of-tremor_tbl1_259567231

Shahir, A. (2017). Differential diagnosis of tremors. Retrieved from https://www.slideshare.net/ahmadshahir18/differential-diagnosis-of-tremors-73335545

Stanford Medicine 25. (2013). Know your tremor. Retrieved from https://stanfordmedicine25.stanford.edu/blog/archive/2013/Know-your-tremor.html

Tremor. (n.d.). D54581F5-F3F0-43F9-8781-ADED81C6ABCC[1].pdf

Tremor. (n.d.). C6DF2978-42CC-4F8A-89D2-B661C1B2BE1D[1].pdf

University of California, San Francisco. (n.d.). Movement Disorders and Neuromodulation Center. Retrieved from https://movementdisorders.ucsf.edu/conditions--treatments/tremor

University of Pennsylvania. (n.d.). The Fling project. Retrieved from https://fling.seas.upenn.edu/

WebMD. (n.d.). Tremors: Essential tremor and other types of tremor. Retrieved from https://www.webmd.com/brain/essential-tremor-and-other-types-of-tremor

Xu, J., Zhang, C., Gao, X., Song, Y., & Chen, H. (2023). 4D printing of soft orthoses for tremor suppression. Applied Nanoscience, 13(3), 853–860. https://doi.org/10.1007/s42242-022-00199-y

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