Low-cost technology may improve rehab for stroke victims
Wearable sensors help patients relearn skills, while clinicians get data on progress.
New technology being developed at the Tandon School of Engineering at New York University is designed to help stroke victims more quickly regain lost motor skills compared with conventional therapies.
The technology, projected to cost $1,000 for each unit, can be placed in patient homes, negating the need for frequent trips to a hospital or clinic for rehabilitation.
The project uses “mechatronic devices,” which is a marriage of mechanical and electrical engineering disciplines to make smart products with embedded intelligence, says Vikram Kapila, a professor of mechanical and aerospace engineering at NYU’s Tandon School of Engineering. An example of such devices is airbags in a car, he explains. Sensors detect a crash, and the bags deploy.
Stroke patients often lose functionality in their arms and hands; it is difficult to pick up a glass or to know if enough pressure is being placed on the glass to keep it from falling. A patient may have lost functionality in the right hand, but has functionality in the left hand.
The concept behind the project is to start with the good left hand doing a task and then transfering data collected by wearable mechatronic devices to the right hand. These devices include a jacket to measure arm placement and a glove to measure wrist and finger placement and finger joint angles. Other measures, such as grasping force and lifting force, also are collected.
When a patient performs an exercise, such as lifting a water bottle, microcontrollers quantify the action and measure grip strength, with information displayed on a small computer-like tabletop device that enables a patient and clinicians to see the force being applied to lift the bottle or do a different task.
Wearing a jacket embedded with sensors, a patient will use the good left hand to lift the bottle with the force of lifting and grasping charted. If too much force is applied, a ball on the tabletop device will turn red. If medium proper force is applied, the ball will turn yellow, and if proper force is applied, the ball will turn green. The key is to try to replicate those measures with the disabled right hand.
With repetition, doing the tasks with the good left hand over time will enable the brain to transfer information from the left hand to the right hand so it can do the same task. Data collected by smartphone also can be transmitted to a physician or physical therapist to track progress and change therapy procedures if necessary. There are separate modules for these exercises covering the hand, arm and fingers.
The emerging technology also has a financial benefit for physicians and therapists, Kapila says. A clinician can do one rehabilitation treatment at a time in an office and bill once for the treatment. But if multiple patients are at home doing the rehabilitation and sending results to a clinician via email or a text image, the clinician can bill for each of those home-based rehab sessions.
The project is currently being conducted by students and faculty, but funds are being sought to move the idea from the lab to a pilot project with rehabilitation clinics and patients in their homes, after which feedback will be collected and any necessary improvements will be made. The goal is to have 50 devices being piloted. All materials, including smartphones, lithium batteries and sensors are off the shelf or open source products.
Just in the United States, the project has the potential to serve 300,000 patients annually, Kapila says, and once commercialized the hope is to get 1 or 2 percent of that market in the first year after receiving regulatory approvals.
The technology, projected to cost $1,000 for each unit, can be placed in patient homes, negating the need for frequent trips to a hospital or clinic for rehabilitation.
The project uses “mechatronic devices,” which is a marriage of mechanical and electrical engineering disciplines to make smart products with embedded intelligence, says Vikram Kapila, a professor of mechanical and aerospace engineering at NYU’s Tandon School of Engineering. An example of such devices is airbags in a car, he explains. Sensors detect a crash, and the bags deploy.
Stroke patients often lose functionality in their arms and hands; it is difficult to pick up a glass or to know if enough pressure is being placed on the glass to keep it from falling. A patient may have lost functionality in the right hand, but has functionality in the left hand.
The concept behind the project is to start with the good left hand doing a task and then transfering data collected by wearable mechatronic devices to the right hand. These devices include a jacket to measure arm placement and a glove to measure wrist and finger placement and finger joint angles. Other measures, such as grasping force and lifting force, also are collected.
When a patient performs an exercise, such as lifting a water bottle, microcontrollers quantify the action and measure grip strength, with information displayed on a small computer-like tabletop device that enables a patient and clinicians to see the force being applied to lift the bottle or do a different task.
Wearing a jacket embedded with sensors, a patient will use the good left hand to lift the bottle with the force of lifting and grasping charted. If too much force is applied, a ball on the tabletop device will turn red. If medium proper force is applied, the ball will turn yellow, and if proper force is applied, the ball will turn green. The key is to try to replicate those measures with the disabled right hand.With repetition, doing the tasks with the good left hand over time will enable the brain to transfer information from the left hand to the right hand so it can do the same task. Data collected by smartphone also can be transmitted to a physician or physical therapist to track progress and change therapy procedures if necessary. There are separate modules for these exercises covering the hand, arm and fingers.
The emerging technology also has a financial benefit for physicians and therapists, Kapila says. A clinician can do one rehabilitation treatment at a time in an office and bill once for the treatment. But if multiple patients are at home doing the rehabilitation and sending results to a clinician via email or a text image, the clinician can bill for each of those home-based rehab sessions.
The project is currently being conducted by students and faculty, but funds are being sought to move the idea from the lab to a pilot project with rehabilitation clinics and patients in their homes, after which feedback will be collected and any necessary improvements will be made. The goal is to have 50 devices being piloted. All materials, including smartphones, lithium batteries and sensors are off the shelf or open source products.
Just in the United States, the project has the potential to serve 300,000 patients annually, Kapila says, and once commercialized the hope is to get 1 or 2 percent of that market in the first year after receiving regulatory approvals.
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