Wearable, AI-assisted UltiGesture May Curb Gait Freezing in Parkinson's

An interdisciplinary research team from William and Mary University and Virginia Commonwealth University (VCU) is programming artificial intelligence to provide a wearable device to treat gait freezing (FoG), the temporary inability to move while walking, which is a motor symptom develop Parkinson's disease.

“Freezing the aisle can be very isolating socially. It is very stressful, or at least stressful, for family members who have to help their loved ones. It affects their psyche through the fear of falling, ”Ingrid Pretzer-Aboff, PhD, Associate Professor and Senior Nursing Scientist at the VCU School of Nursing, said in a press release.

The program to be developed focuses on the combination of the use of software (computer programming) and hardware (wearable devices) to deliver targeted vibrations in response to certain Parkinson's symptoms such as tremors or freezing gait.

“There are very few ways to help patients like this. We hope that using vibration in this new way will lead to better results and give people some hope, a little more autonomy, freedom and a better quality of life, ”added Pretzer-Aboff.

The freezing of gait episodes can be triggered by environmental and psychological factors such as: B. starting to walk, walking through narrow spaces, changing direction while walking, approaching a visual target, or doing something else while walking. Time-critical situations, such as entering an elevator before closing the doors, can also trigger an episode.

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"Each person with Parkinson's disease is unique in terms of their sensitivity to these various triggers, which underscores the need for tailored therapeutic approaches," the researchers wrote in their funding application to the National Institutes for Health, which provided the funding.

"Hence, a better understanding of the modifiable factors underlying FoG and a better understanding of the individual nuances of FoG's experience is warranted," they added.

One of the researchers helped. From August to December 2020, Ken Koltermann, a PhD student associated with the project, walked on a gait monitoring mat used in clinics, the Protokinetics Zeno Walkway. He then compared the data obtained from the mat with data he had collected using an UltiGesture tape, a piece of hardware with a gyroscope and accelerometer developed by Gang Zhou, PhD, a computer science professor at William and Mary University became.

The UltiGesture tape allows researchers to measure both the acceleration of the person wearing the tape via their accelerometer and the person's rotational speed via their gyroscope. This data can then be transferred to a smartphone via Bluetooth. Further programming, including artificial intelligence, is then used by an app on the phone to detect both the basic gait (or the wearer's gait) and any anomalies in the person's gait.

The data Koltermann collected enabled researchers to advance and develop machine learning software that classifies his walking. Using the Protokinetics Zeno Walkway mat, researchers were able to validate the UltiGesture tape and associated software.

"If we can show that our device is as accurate as the mat, it could lead to a revolution in accessibility for healthcare - and not just for Parkinson's," said Koltermann.

"This will make gait analysis so much more accessible, especially for rural health systems and low-income areas," he added, given the price difference between the tape and the mat - $ 10 versus $ 50,000.

The next step is to pair the UltiGesture system with the VibeForward device, a small piece of hardware developed by Resonate Forward that delivers localized vibration to the ankle and foot to encourage movement in those with walking or stabilization problems.

Eventually, using the UltiGesture system with VibeForward, the device can sense the slightest freeze in the aisle as a person walks and create a vibration at the ankle and foot level that allows the wearer to keep moving.

"This system will be able to differentiate between intentionally stopping and stopping involuntarily by freezing the aisle, and then it will be able to provide instant vibration treatment," Zhou said.

Another element of research, which is still in its early stages, is a plan to incorporate environmental stimuli into the data that will enable artificial intelligence to identify possible triggers for freezing of corridor events, including elevators and doors.

“It's really about giving Parkinson's patients a new level of freedom to navigate the world safely. … Giving patients that freedom is a motivating factor here, ”said Zhou.

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