A DEVICE TO OBJECTIVELY MEASURE WRIST FLEXIBILITY HELPS OPTIMISE DEEP BRAIN STIMULATION FOR PARKINSON’S DISEASE
Parkinson’s disease is a neurodegenerative disorder caused by the loss of neurons that make dopamine. This dopamine loss causes tremor, instability and rigid joints, amongst other symptoms. A treatment option when symptoms progress, or if patients stop responding to drugs, is deep brain stimulation (DBS). This involves permanently implanting electrodes into the brain to neutralize symptoms.
During DBS surgery, the electrodes are carefully positioned and calibrated to make sure that symptoms are effectively neutralized. To check this, neurologists manipulate the wrist to see whether the electrode set-up improves wrist rigidity, with more flexibility indicating that the electrodes are well positioned and calibrated. “This method is very subjective and depends on the experience of each doctor,” says Duarte Dias, a biomedical engineer in the iHandU team at INESC TEC and Faculty of Engineering, University of Porto. “So our goal was to overcome this limitation.”
Creating a solution
The team started work in 2015 to find a way to quantitatively measure the level of wrist rigidity in people with Parkinson’s undergoing DBS. Their solution – called the iHandU system - is a textile wrist band studded with a gyroscopic sensor that feeds data in real time via bluetooth into a smartphone algorithm. This application uses a patented computer method1 to classify wrist rigidity in real-time. This classification algorithm calculates the wrist rigidity improvement during DBS. In tests, the iHandU system had an average of 80% agreement with two blinded expert doctors, who manually manipulated the patient’s wrist and gave their subjective rigidity scores.
The patented algorithm and wrist rigidity model that classifies signals from the wristband form “the core of the project,” according to Dias. The algorithm has already gone through several iterations to improve issues such as how to deal with intermediate wrist rigidity and the speed of data processing. The wristband has also evolved throughout the project, resulting in a slimmer, more comfortable wearable. The user interface of the smartphone app, which displays the wrist rigidity in real-time, was adapted to be more user friendly.
“The classification model was tested at three different times, so there are three different datasets,” says project researcher, Elodie Múrias Lopes, “altogether 45 patients were used to train the system.”2 So far, the system has been used in around 100 patients in Portugal, generating a total of 1600 classifications and 107 minutes of data acquisition.
THE PATENTED ALGORITHM ...
[IS] THE CORE OF THE PROJECT
The iHandU system is in its fourth iteration, and the team is already working on version 5. “We are improving the sensor and the algorithm,” says Dias, “we should try to have a system that is better adapted to the conditions and the clinical environment.” Planned improvements include redesigning and shrinking the sensor hardware, and reducing the energy requirements of sending data to the smartphone via Bluetooth.
The team plan to generate more clinical data throughout 2020, with a multi-centre clinical trial planned at hospitals in the Netherlands, the UK and Germany. “We will then apply to certify this as a medical device to ensure that we can comply with medical device regulatory approval,” says Dias.
The team imagine a myriad of future applications for iHandU, such as assessing disease progression, monitoring patients at home, assessing other symptoms of Parkinson’s such as tremor, or even evaluating the effectiveness of new medicines for Parkinson’s during clinical trials. The system also has scope to monitor other neurological and musculoskeletal movement disorders such as epilepsy and rheumatoid arthritis.
The shape of success
According to Dias, the success of the project to date is thanks to the strength of the interdisciplinary team, including biologists, engineers, and IT and electronics specialists. Múrias Lopes herself is a physicist, turned biomedical engineer. “Biology is my second favorite field - after physics,“ she laughs. Having such varied expertise to draw on has helped the team overcome several hurdles.
Dias recommends that researchers starting out in a medical device project start thinking about forming a multidisciplinary team, right from the start. “You need a strong connection with the hospital to move on with the idea, to get some data, and to test and validate your idea,” he says. His next recommendation is that “once you create that knowledge and prove that it works, try to protect it with patents.” Once that is in place, Dias advocates publishing the research in high-impact journals. “This can give you visibility as a researcher, and can also give visibility to the idea for further funding and commercial exploitation.”
João Paulo Trigueiros da Silva Cunha, Pedro Costa. Wrist rigidity assessment device for use in deep brain stimulation surgery. Patent WO2016166702A1. Octobre 20, 2016.
Lopes et al, Sensors 2020, 20(2), 331; https://doi.org/10.3390/s20020331