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Parkinson Smart Cane

An instrumented cane that generates visual, auditory and tactile cues to help with a condition called Freezing of Gait experienced by those suffering from Parkinson's Disease .

  • Final prototype of the cane.

  • Video demo of the device in action.

    Video demo of the device in action.

  • Components of the smart cane.

  • Block diagram of the electronic system.

  • Algorithm to trigger the gait assist system.

  • Gait assist system worn by a test subject.

What it does

Patients with Parkinson's disease suffer from a condition known as Freezing of Gait (FoG) which causes a pause in walking despite the intention to walk. The device described helps patients overcome FoG through visual, auditory and tactile sensory cues.


Your inspiration

Research indicates sensory feedback (when Freezing of Gait occurs) can show improvement in the condition. Three main approaches appear in literature: 1. Visual cues - where the patient is given visual feedback about walking progress. 2. Auditory cues - Such as a rhythmic sound is played back at the step speed. 3. Tactile cues - where a rhythmic vibration is used to stimulate normal walking or applied when freezing is detected. The main shortcomings of current methods are their lack of portability. The device described attempts to combine multiple sensory feedback methods into a portable, commonly used walking aid (a cane).


How it works

The device is an instrumented cane. It uses a combination of force sensitive resistors on the cane handle and an inertial measurement unit (measures acceleration, angular velocity) to detect the Freezing of Gait. When freezing of gait is detected, the device uses three methods to give sensory feedback to the patient. A laser pointer with a cylindrical lens projects a guiding line on the floor to give visual feedback. A buzzer embedded in the cane handle generates a beeping tone to provide auditory feedback. Three vibration motors are used. One is embedded into the handle of the cane. Two are embedded into a strap-on cloth cuff that is attached at the calf. The vibration motors play back an adjustable rhythmic beat.


Design process

Central to the device is the detection of Freezing of Gait (FoG). When FoG occurs, walking becomes unstable and causes increased load on the cane. Trembling hands are also strongly associated with occurrence of FoG. To detect these conditions, three force sensitive resistors along the surface of the cane handle measure the pressure of the hand and an IMU (Inertial Measurement Unit) in the handle measures acceleration and angular velocity. Increasing or steady large pressure on the handle and large amplitude oscillations in the handle gyroscope measurements (detected by counting zero crossings) trigger the systems to assist with FoG. The force sensors on the handle also decide when to turn the system off if the cane is not being held. An initial prototype mounted the wiring externally. While functional, it posed risks of the wires being damaged by being caught on objects. For the second prototype a hollow steel cane was used as it allowed routing the wiring from the sensors, vibration motor and buzzer (embedded in the handle), the laser diode (mounted midway along the cane shaft) and an Arduino micro-controller. To keep the device portable, the two vibration motors strapped to the calf are powered independently and controlled over a wireless RF (Radio Frequency) link.


How it is different

Most devices that provide sensory cueing/feedback for FoG are research devices. Many of these methods are not portable and cannot be used outside the lab environment. Additionally, most devices use cues of a single type: visual, auditory or tactile. Some portable devices are already on the market such as Agilitas, Path Finder, Walk to Beat and Walk Aid. However, as far as we know, no device on the market exists that integrates all three forms of sensory cueing to overcome FoG. Our Parkinson Smart Cane integrates visual, tactile and auditory feedback into a self contained, portable device.


Future plans

Currently, the system has only been tested on healthy subjects emulating the pattern of walking of PD patients. The next step is to test and validate the system in with real patient data. Additional improvements can also be made in usability such as the inclusion of an emergency button that notifies family/medical help along with location tracking. The accuracy of the detection of FoG can also be improved by collecting more patient data and using it to inform better detection algorithms.


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