Living with pain and Parkinson's developing an understanding of the impact, trajectory and pain management needs: a qualitative interview study protocol.

Introduction: Pain is reported as one of the most troubling symptoms for people with Parkinson's (PwP); however, the literature exploring their lived experience of pain and how to manage it is limited. Pain affects PwP at all stages of their condition and can fluctuate and change over time. Therefore, it is pertinent to speak to PwP to understand their experiences of pain to inform the development of tailored behavioural interventions to manage pain.

Self-supervised learning of wrist-worn daily living accelerometer data improves the automated detection of gait in older adults.

Progressive gait impairment is common among aging adults. Remote phenotyping of gait during daily living has the potential to quantify gait alterations and evaluate the effects of interventions that may prevent disability in the aging population. Here, we developed ElderNet, a self-supervised learning model for gait detection from wrist-worn accelerometer data.

Profiling people with Parkinson's disease at risk of cognitive decline: Insights from PPMI and ICICLE-PD data.

Introduction: A subset of people with Parkinson's disease (PD) develop dementia faster than others. We aimed to profile PD cognitive subtypes at risk of dementia based on their rate of cognitive decline.

Method: Latent class mixed models stratified subtypes in Parkinson's Progression Markers Initiative (PPMI) (= 770) and ICICLE-PD (= 212) datasets based on their decline in the Montreal Cognitive Assessment over at least 4 years.