The STRAT-PARK cohort: A personalized initiative to stratify Parkinson's disease.

The STRAT-PARK initiative aims to provide a platform for stratifying Parkinson's disease (PD) into biological subtypes, using a bottom-up, multidisciplinary biomarker-based and data-driven approach. PD is a heterogeneous entity, exhibiting high interindividual clinicopathological variability. This diversity suggests that PD may encompass multiple distinct biological entities, each driven by different molecular mechanisms. Molecular stratification and identification of disease subtypes is therefore a key priority for understanding and treating PD. STRAT-PARK is a multi-center longitudinal cohort aiming to recruit a total of 2000 individuals with PD and neurologically healthy controls from Norway and Canada, for the purpose of identifying molecular disease subtypes. Clinical assessment is performed annually, whereas biosampling, imaging, and digital and neurophysiological phenotyping occur every second year. The unique feature of STRAT-PARK is the diversity of collected biological material, including muscle biopsies and platelets, tissues particularly useful for mitochondrial biomarker research. Recruitment rate is ∼150 participants per year. By March 2023, 252 participants were included, comprising 204 cases and 48 controls. STRAT-PARK is a powerful stratification initiative anticipated to become a global research resource, contributing to personalized care in PD.

A practical efficient human computer interface based on saccadic eye movements for people with disabilities.

Human computer interfaces (HCI) provide new channels of communication for people with severe motor disabilities to state their needs, and control their environment. Some HCI systems are based on eye movements detected from the electrooculogram. In this study, a wearable HCI, which implements a novel adaptive algorithm for detection of saccadic eye movements in eight directions, was developed, considering the limitations that people with disabilities have. The adaptive algorithm eliminated the need for calibration of the system for different users and in different environments. A two-stage typing environment and a simple game for training people with disabilities to work with the system were also developed. Performance of the system was evaluated in experiments with the typing environment performed by six participants without disabilities. The average accuracy of the system in detecting eye movements and blinking was 82.9% at first tries with an average typing rate of 4.5cpm. However an experienced user could achieve 96% accuracy and 7.2cpm typing rate. Moreover, the functionality of the system for people with movement disabilities was evaluated by performing experiments with the game environment. Six people with tetraplegia and significant levels of speech impairment played with the computer game several times. The average success rate in performing the necessary eye movements was 61.5%, which increased significantly with practice up to 83% for one participant. The developed system is 2.6×4.5cm in size and weighs only 15g, assuring high level of comfort for the users.