Amviewlate: Enhancing mobility in people with Parkinson's disease



challenge  |  exploratory research  |  ideation & prototyping  |  final concept

FINAL CONCEPT

Through guerrilla research of academic papers and testimonials, as well as paper prototyping AR interactions, our team analyzed and addressed specific problems unique to people with Parkinson’s.


FINAL CONCEPT
at a glance

Deliverables:
Introducing Amviewlate
Amviewlate is an AR prototype that projects visual cues in augmented reality to facilitate walking and interacting with objects. A riff on "ambulate" and "view", Amviewlate assists with two key problems: Freezing of gait, an ambulatory disturbance that results in slow, shuffled walking, and dyskinesia, the impairment of voluntary movement, particularly without stimuli to trigger reflexes.

A staircase illusion helps simulate the act of climbing stairs, enabling continuous motion. A visual cue guides the hand to an intended target. All actions are governed by voice control software to enable full agency in users with limited gesture control. Through Amviewlate, we hope to restore mobility, independence, and confidence to users.

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How it works
This project was built with an AR application using Google Cardboard, a marker recognizer library called Vuforia, and Android Speech Recognizer. It was important to us to incorporate voice controls to help people with Parkinson’s — who have trouble with precise gesture controls — navigate the AR experience. There were no free Android speech recognizer assets available on Unity, so we built one ourselves by integrating Android plug-ins to the Unity project.
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amviewlate storyboard
Moving forward
More than 10 million people worldwide are living with Parkinson's disease. Parkinson’s patients have trouble controlling their movements, from reaching for objects to simply walking across the room. These problems lead to loss of independence and reduced quality of life: Sufferers often avoid activities outside of the home, leading to isolation and depression.

While Google Cardboard has the benefit of requiring lightweight, affordable technology (a smartphone and a mobile headset), the spatial recognition capabilities are limited. In our demo, we got around this by using the Vuforia library to trigger AR effects based on image targets placed throughout a space. However, using AR headsets with spatial recognition would enable us to generate the AR effects dynamically using computer vision to recognize paths, passageways, and obstacles in an environment. Luckily, better spatial recognition is within reach with the next generation of AR headsets, such as the Hololens or Metavision.

amviewlate projection
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