Wearable Leg Sensors Accurately Detect Parkinson’s Freezing of Gait

Steve Bryson, PhD avatar

by Steve Bryson, PhD |

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Placing sensors on the lower leg to measure acceleration and orientation with movement was the best way to detect freezing of gait symptoms in people with Parkinson’s disease, a small study suggested.

These findings could be helpful for screening and treating freezing gait at early stages, the researchers noted.

The study, “Recognition of freezing of gait in Parkinson’s disease based on combined wearable sensors,” was published in the journal BMC Neurology.

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Freezing of gait (FoG) is a common complication of Parkinson’s disease. It is characterized by an inability to lift the foot and take a step, as if the feet are stuck to the floor. FoG often occurs when the patient starts to walk, turn, or pass obstacles, and can lead to falls and bone fractures, affecting quality of life.

As its early identification and evaluation is considered essential, wearable devices to detect FoG are needed, the researchers wrote.

Ways to detect FoG have been evaluated based on computer algorithms and sensors placed at different locations on the body, but finding a reliable system for use in daily life has been difficult.

Researchers at Gyenno Science in China compared the performance of different sensor configurations to determine the optimal features of a highly effective system for evaluating FoG in Parkinson’s.

Their study recruited 12 people with Parkinson’s who experienced FoG daily, 10 men and two women with a mean age of 66.75. All were receiving Parkinson’s medications and had no signs of cognitive impairment.

To measure FoG, sensors were placed on the waist, thighs, shanks (lower leg just above the ankle), and feet (outside the shoes). Thin-film sensors were also inserted into the shoe beneath the heel and right and left insoles. Participants completed a random gait test and a timed up and go (TUG) test, in which they stood up from a chair, walked forward and then back to the seat, more than three times.

A FoG episode was defined when the patient was instructed to walk but had not yet stepped forward, while the end of the episode was defined as the time when an effective step took place, followed by a continuous normal walk. Data collected by the sensor was wirelessly transmitted to a computer for analysis, and a time-synchronized video of each test was recorded.

Among the 12 participants, 10 showed FoG during the tests for a total of 276 FoG episodes assessed from the video recordings. FoG episodes ranged from 0.9 to 76.9 seconds, with more than 50% lasting for less than six seconds and 93.5% lasting less than 20 seconds.

According to data for single sensor positions, the accelerometer, which measures acceleration, on the left thigh achieved the optimal effect. The accelerometer and gyroscope, measuring orientation, on the shin and waist also generated positive detection results.

Overall, sensors on the leg and the waist were better at detecting FoG than those on the foot and the sole. In addition, the accelerometer on the leg and the waist outperformed that of the gyroscope.

Researchers noted that the lower leg is more convenient than the thigh in wearing a sensor, and the shank can be used to place the accelerometer or the gyroscope. But as precision scores for a single sensor were lower than a dual configuration, like a left shank plus waist sensor, “optimal performance may not be obtained with a single sensor.”

The team then evaluated data from multiple sensors and positions. The combination of the left shank gyroscope and accelerometer was better than a single sensor, and was similar to that of the waist and left shank combination.

Accounting for all factors, including detection performance, cost, and actual sensor deployment, the left shank accelerometer and gyroscope combination was considered the optimal sensor configuration. This position yielded an 88.09% accuracy in detecting FoG, as well as a 78.39% sensitivity, meaning the test’s ability to identify FoG correctly, and a 91.66% specificity, the ability of the test to rule out FoG correctly.

“This research method can assist [Parkinson’s disease] patients to resume walking and normal activities; it can also offer information about FoG symptoms as well, playing a guiding role in FoG research and treatment,” the researchers concluded.

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