REAL_PD

Today*s management of patients with a chronic disorder like Parkinson*s disease
(PD) is imperfect. Our understanding of clinical profiles is based on
observations in small, selective populations with brief follow-up. Moreover,
treatment decisions are based on averaged population results that may not apply
to a specific individual context. These drawbacks will be addressed with a *big
data* approach. Ambulatory sensors will be sued as an objective measure of
patients* performance under everyday circumstances, for longer periods of time.
We aim to explore the potential of using longitudinal ambulatory data to enrich
a standardized clinical dataset, which reflects current clinical practice for
the assessment of disease status.

The study will be conducted in two sequential phases. In the first phase 5-7
physiotherapists and 20 subjects with Parkinson*s disease will be enrolled to
test the feasibility of the study protocol to evaluate the value of ambulatory
sensor monitoring. In the second phase, 250 physiotherapists and 1000 patients
will be included. The current study protocol covers the first pilot phase only.
The aims of this pilot are: (a) to test our ability to identify motivated
therapists; (b) to get a feeling for the ease and speed of recruitment per
therapist; (c) to test the feasibility (mainly the time needed for the
assessments) and quality of the baseline clinical assessments by the
therapists; (d) to test the patients* experiences with the ambulatory devices,
and to create an impression for their compliance in everyday life; and (e) to
field-test the data streaming from the ambulatory devices to the Intel
platform.

This is an observational study. 5-7 ParkinsonNet physiotherapists will identify
20 eligible patients from their practice. The physiotherapist first performs a
standardized clinical assessment, based on the PPMI protocol
(www.ppmi-info.org). This assessment will last for 60 minutes. Next, patients
will be asked to wear a wrist watch that contains accelerometers, combined with
a smartphone, during day and night, for 4 weeks. The sensor consists of a wrist
watch (with tri-axial accelerometers). The smartphone is used to transmit data
the de-identified accelerometer data to a data platform. The physiotherapist
will act as a personal coach during this period.

The data platform is owned by the MJFF and managed by Intel, who developed a
dedicated data analysis platform for ambulatory data. Intel will receive
de-identified data only.

Patients will have a baseline PPMI assessment, 2 call from the research team to
ask for the experiences with the devices (after 1 and 3 weeks), and a
face-to-face meeting after 2 weeks with their therapist to discuss feasibility,
possible barriers, as outcomes of the recordings. After completion of the
4-week follow-up phase patients will complete a written evaluation form about
the use of the sensor and the support offered by the physiotherapist. For
examining daily functioning, a self-monitoring App on the smart phone asks for
answers on two simple questions: medication intake and how they are feeling in
general.

First, data will be recorded 24/7, for total duration of 4 weeks. Second, data
will be transmitted to a data platform developed and managed by Intel. This is
an open access platform, though patients remain ownership over their own data,
and remain in control in regards to which data can be shared for research
purposes. They will be asked for permission to share the raw data in a
de-identified form for analysis and use in future publications in the informed
consent form.
Both of the above-mentioned issues can give a breach of privacy. However, the
feasibility of this approach has been demonstrated by our research partners in
the FP7-funded SensePark project, which demonstrated that patients are able and
willing to wear multiple ambulatory devices, given they remain owner of their
own data.