Publications

We are pleased to share that Magnes presented new clinical findings at the 7th World Parkinson Congress 2026. Our poster, developed in collaboration with Queensland University of Technology (QUT), explored the effects of smart shoe-based vibrotactile cueing on gait performance in people living with Parkinson’s disease and freezing of gait. Key findings presented included: Improved gait velocity and heel clearance Reduced gait variability and enhanced stability Persistent post-cueing effects beyond active stimulation The study analyzed more than 1,100 strides across multiple gait conditions, reinforcing the potential of wearable neurotechnology to support real-world mobility and objective movement assessment. We are proud to have contributed to the growing body of evidence supporting digital mobility solutions in Parkinson’s care and were grateful for the opportunity to engage with clinicians, researchers, industry leaders, and members of the Parkinson’s community at WPC 2026 in Phoenix. #WPC2026 #Parkinsons #DigitalHealth #MedTech #Neurotechnology #Mobility #ClinicalInnovation #WearableTechnology

At the 7th World Parkinson Congress 2026, clinical findings were presented from a case study developed and conducted in collaboration with Parkinson Wellness Recovery (PWR!) in Tucson, Arizona, evaluating the use of NUSHU smart shoes and adaptive vibrotactile feedback during a four-session gait rehabilitation program for a person living with Parkinson’s disease and significant freezing of gait (FOG). The study demonstrated measurable improvements across multiple mobility outcomes, particularly during cognitively demanding dual-task scenarios where freezing of gait symptoms are often more pronounced. Key findings included: Reduced freezing of gait scores during vibrotactile cueing sessions Improved gait performance under cognitive load Reinforcement of rehabilitation training effects through adaptive real-time feedback These findings contribute to the growing body of evidence supporting wearable, data-driven rehabilitation technologies designed to enhance mobility and support real-world Parkinson’s care. We were pleased to share these results with clinicians, researchers, rehabilitation specialists, industry leaders, and members of the Parkinson’s community at WPC 2026 in Phoenix. #WPC2026 #Parkinsons #Neurorehabilitation #DigitalHealth #MedTech #WearableTechnology #Mobility #ClinicalInnovation

Automatic methods for detecting FOG using the freeze index (FI) have been widely proposed to systematically monitor FOG in real life and guide therapy optimizations. However, methods to estimate the FI have relied on a broad range of measurement technologies and computational methodologies, often lacking mathematical rigor. This lack of standardization has severely hindered the acceptance of FI by regulatory agencies as a reproducible, robust, effective and safe measure on which to base further developments. In this study, we formalize the definition of the FI and propose a rigorous, explicit estimation algorithm, which may serve as a standard for future applications. This standardization provides a consistent and reliable benchmark.

Motion capture systems are widely accepted as ground-truth for gait analysis and are used for the validation of other gait analysis systems. To date, their reliability and limitations in manual labeling of gait events have not been studied. Objectives: Evaluate manual labeling uncertainty and introduce a hybrid stride detection and gait-event estimation model for autonomous, long-term, and remote monitoring. Methods: Estimate inter-labeler inconsistencies by computing the limits-of-agreement. Develop a hybrid model based on dynamic time warping and convolutional neural network to identify valid strides and eliminate non-stride data in inertial (walking) data collected by a wearable device. Finally, detect gait events within a valid stride region.