BOSTON--(BUSINESS WIRE)--Pison, the pioneers behind AI-powered neural biosensors for health, wellness, and 3D touchless smart device control, today announced the results of recent clinical trial conducted by researchers at the Lewis Katz School of Medicine at Temple University’s MDA/ALS Center of Hope. The trials concluded that Pison’s Neural Biosensor hardware and electroneurography (ENG) technology was able to distinguish patients with amyotrophic lateral sclerosis (ALS) from a healthy population and detect changes in surface electromyography (sEMG) in ALS patients which reflects motor neuron changes and is correlated with functional changes. These results demonstrate that Pison’s technology has the potential to become a digital biomarker to detect neurological diseases, monitor progression, and inform treatment.
In addition, Pison’s ongoing efforts to embed their technology into wearable devices, such as smart watches, opens the door for continuous monitoring of patients and even pre-symptomatic populations.
The study, funded by The ALS Association and the National Science Foundation and led by Dr. Terry Heiman-Patterson, professor of neurology and director of the MDA/ALS Center of Hope at the Lewis Katz School of Medicine at Temple University, used Pison’s technology to classify electromyography activity and fasciculations in patients in the early stages of ALS. The study found that Pison’s technology could distinguish between patients diagnosed with ALS and a healthy population.
“New and better ways to diagnose and monitor people with ALS are urgently needed,” said Dr. Kuldip Dave, senior vice president of research at The ALS Association. “We are proud to have supported the initial testing of this promising new technology. We look forward to seeing the results of future studies to confirm and validate these findings with larger groups of participants.”
Pison’s measurements correlated with disease progression and could augment the ALS Functional Rating Scale (FRS), the most widely accepted measure of functional status, for evaluating patients with ALS. The technology demonstrated that it could detect fasciculations and differentiation between healthy people and people living with ALS in a resting state using deep learning algorithms. Based on this result, the Pison technology presents an opportunity for doctors to collect actionable information about motor neuron health passively and non-intrusively. This opens the door for in-home longitudinal monitoring and data collection of diagnosed patients and even monitoring healthy populations.
“If these results are validated, then this will enable clinicians to detect motor neuron involvement non-invasively and track it over the course of disease and with treatment interventions. Further, this technique may enable earlier diagnosis of motor neuron damage in presymptomatic gene carriers, help to detect motor neuron involvement in other disorders and provide a system that can remotely monitor progression in ALS and help in patient-centric clinical trial design,” said Heiman-Patterson.
The landmark finding has implications for a continuous, non-interventional form of ALS tracking and diagnosis which could perhaps even replace the current standard of intermittent clinical evaluations and patient surveys. The finding may also advance development of new treatments by passively and accurately measuring patient responses to experimental interventions.
“This finding is truly transformational. It will both enable clinical diagnosis for patients early in the course of their disease where treatments may be more efficacious, and also enable real time tracking of disease progression. Importantly, this ability to follow patients closely will allow health providers to monitor responses to therapy and individualize treatment, which will ultimately lead to improved patient outcomes,” said Dr. William Brian Gormley, Director of Neurosurgical Critical Care at Brigham and Women’s Hospital, and Associate Professor at Harvard Medical School.
Pison is currently planning larger, multi-year studies to further quantify and confirm the technology’s potential for early diagnosis and symptom tracking in ALS and other neuromuscular degenerative diseases, including multiple sclerosis and Parkinson’s disease.
“We see many opportunities to apply Pison’s technology to enhance the health and wellness of millions of people – those diagnosed with neurological disease and people who want to improve their mental performance,” said John Croteau, CEO of Pison. “This clinical result is an important step towards receiving regulatory approval for medical applications of Pison technology. We have begun licensing our Neural Biosensor for incorporation into popular wearables such as smartwatches and fitness trackers for passive health monitoring, which will ultimately have the ability to track ALS and other neurological disorders in the form of neural health apps and telehealth services.”
To learn more about Pison, visit www.pison.com.
About Pison Technology
Pison has pioneered the use of a passive, neural biosensor at the wrist and patented machine learning algorithms—an AI technique called electroneurography (ENG)—to translate physiological electricity generated by the brain into machine interpretable events in software. Founded in 2016 with grants from the Massachusetts Institute of Technology, National Science Foundation, and ALS Association, Pison started out helping patients with neurodegenerative disorders navigate the world. Soon, any smartwatch embedded with Pison’s biosensor will tap your nervous system to improve your health, fitness and control smart devices at home, on the go, in the Metaverse — and even on the battlefield.
About Lewis Katz School of Medicine at Temple University MDA/ALS Center of Hope
The MDA/ALS Center of Hope at the Lewis Katz School of Medicine at Temple University is a multidisciplinary ALS clinic serving the greater Philadelphia Region since 2016. The center is dedicated to excellence in clinical care of people living with ALS with a patient centric approach. The center also actively participates in clinical research including trials, tissue banking, natural history studies, and research leveraging technologies.