Phase 2
There’s No Place Like Home
Traditional assessments of PD and PSP take place in clinic. Similar to the set up of Phase 1, patients would attend in-person to be assessed by movement specialists, be prescribed any changes in their medication regimen, and discuss any concerns they may have. In 2020, the CoVID-19 transformed the clinical landscape, preventing many patients from attending their scheduled clinics and leaving the health sector (much like the rest of the world) to scramble to adapt.
Phase 1 of the study was completed prematurely as a result of the pandemic, but it provided the study a unique opportunity to evolve. The use of digital technology provides the capacity to perform assessments anywhere, provided the technology is simple enough to use and there is a reliable network connection. Attending clinics in person can be a stressful and tedious experience; it is time-consuming, disrupts medication regimens, and can be disrupted by a range of factors such as travel disruption and weather conditions. The potential to perform clinical visit at home overcomes these issues, while allowing patients to perform tasks in the comfort of their own residence.
Phase 2 of the OxQUIP study was designed to be entirely remote. Participants attended virtual clinic every four months on Microsoft Teams to perform classic ‘gold standard’ clinical tests (e.g. UPDRS, MoCA, ECAS) over the course of five visits. The digital technology component of the study involved the use of an iPhone and Apple Watch to perform digital sessions on an app with set tasks designed to extract disease-related features. These sessions were completed on a monthly basis for a total of 17 digital sessions.
V = Visit, S = Session
Phase 2 comprised of a total of 130 participants from the following groups:
Group 1 — de novo PD participants i.e. medication–naive
Group 2 — PD participants <8 years since diagnosis
Group 3 — PD participants ≥8 years since diagnosis
Group 6 — HC participants
PSP participants (Group 5) attended four monthly virtual sessions via Teams but were not included in the digital device component of the study.
DBS participants (Group 4) completed the same assessments in-person as previous (see Phase 1).
iPhone 13 Pro Max
Apple Watch Series 7
Commercial devices have been selected for this study for numerous reasons:
A simpler set-up that standard scientific movement sensor equipment (see Phase 1).
Less cumbersome to wear.
Devices in commercial circulation are more accessible for the general public.
Opens the possibility to passive monitoring (below).
In addition to the phone and watch, participants were provided a waist pouch to place the phone into during the balance & walking activities, a charging pad, and a charging plug.
Motion Tracking
The larger cohort of the study take part in monthly digital sessions involving active tasks i.e. measurements are recorded from the phone and watch via the completion of specified tasks. These active tasks are designed to extract specific features expected to be relevant to PD progression
Of additional interest is the capacity to extract disease relevant information over an extended period of time without the need of active tasks. This is referred to as passive monitoring or motion tracking.
A small number of the PD cohort was selected to participant in our Phase 2 Motion Tracking pilot study. Following the completion of their monthly digital sessions, the participants are instructed to continue wearing the Apple Watch throughout the day. Measurements are recorded passively from the Apple Watch throughout the day. At the end of the day, the participants take off the Watch and place it on charge overnight. The next morning, they will sync the data collected from the previous day and then wear the watch again for the full day. The participants are instructed to wear the watch for a full three days.
Passive monitoring is a novel approach to understanding PD. There is much work still to be done to understand the data that is extracted and what it might mean for disease progression. The ability to obtain a greater abundance of data over a longer period of time will allow us to understand the natural progression of PD beyond expectation. We’re excited to continue this work and share it with the wider community.
