For the entire duration of the study, patients will remain under the care of the Early
Palliative Care and Simultaneous Care Outpatient team of the Istituto Nazionale Tumori,
Fondazione Pascale, at home. Pain and other symptoms will be managed according to the
good clinical practice and patients will receive assistance in agreement to the routine
medical care.
The following devices will be used:
Software
Instrumentation
Clinical Assessment Tools: European Organisation for Research and Treatment of
Cancer Quality-of-life Questionnaire Core 30 (EORTC QLQ-C30), Daily Pain Diary, 0-10
numeric rating scale (NRS).
The project will be divided into three main Work Packages (WPs), dedicated respectively
to the creation of the IT infrastructure to support acquisitions (WP1), the patient data
collection campaign (WP2), and the development of machine learning algorithms for
automatic pain recognition (WP3). The application of the devices and verification of
correct functioning will be carried out at the patient's home by the IT staff involved in
the study.
WP1 - The system consists of three main components: the server, with the attached
database, the application for mobile devices, also responsible for managing data
acquisition from physiological signal acquisition devices, and the desktop application,
used by the clinical staff to monitor the progress of data collection.
The mobile application will have the role of interfacing directly with the patient and
acquiring biometric data from wearable devices. Specifically, the following signals will
be acquired: heart rate, body temperature, non-invasive blood pressure, and galvanic skin
response (GSR). The heart rate will be obtained through a wearable device (Garmin
Vivosmart 4) while the body temperature, the non-invasive blood pressure, and the GSR
will be acquired by an external device (a BITalino platform).To further validate the
accuracy of the algorithm that will deal with pain detection, patients will also be given
a QoL questionnaire (EORTC QLQ-C30).
In order to acquire the ground truth of the data, the patient will be asked to provide
feedback on the level of pain, both at certain intervals of time during the day, and in
case of acute pain episodes. This feedback can be based on NRS and multimedia strategies
(e.g., videos). Patients will fill out a daily pain diary.
WP2 - The campaign will include a preliminary acquisition phase aimed at testing the IT
infrastructure. For obtaining an adequate inter-subject and intra-subject variability, it
will be necessary to enroll at least 40 patients, acquiring data for 10-14 days. Thus,
the data collection campaign will be conducted for about 6 months. Each subject will use
the mobile application and sensors for 2 weeks. Data will be acquired using
simultaneously data collection bundles (application, sensors, and any mobile device).
Upon enrolment and at the end, EORTC QLQ-C30 will be administered.
WP3 - The objective is the development of algorithms able to predict the level of pain
perceived by the patient. Having a considerable amount of labelled data available, the
system will learn from the examples.