Use cases

Three major brain diseases and corresponding pilot sites are targeted in ALAMEDA: (a) Parkinson’s Pilot in Greece, at the Movement Disorders Clinic of the First Department of Neurology at Eginition Hospital, Athens University Medical School; (b) MS Pilot by the Italian MS Society Foundation which is the leading funding agency of research in Multiple Sclerosis (MS) field in Italy and the third funding agency worldwide; and (c), patients with stroke at the Neurology Department of University and Emergency Hospital of Bucharest, Romania.

Use Case 1

Study of the use
of sensors in advanced Parkinson’s Disease

Key research question

How to improve the capacity to predict meaningful worsening of either global patient status or specific motor or non-motor aspects of PD?

The care of patients with advanced Parkinson’s Disease (PD) is complex, as both motor and nonmotor manifestations of the disease worsen over time and seriously impair the quality of life of patients and their caregivers. This Use Case will implement a clinical study to assess the use of sensors in monitoring the motor and non-motor aspects of advanced Parkinson’s Disease with the aim to predict the worsening of the manifestations of the desease.

The goal of the Use Case 1 is to correlate in a number of 15 patients with advanced PD the recordings from technology-assisted devices to measurements in classical PD scales, such as the MDS-UPDRS and quality of life-related measures, as well as to correlate simple device recording during sleep to specific PD-related sleep scales and to polysomnographic recordings.

Use Case 2

Multiple Sclerosis and the risk of disease relapse

Key research question

How to improve the capacity to predict relapse risk in MS?

ALAMEDA monitoring ecosystem will provide a breakthrough on multiple sclerosis (MS) management.

Analysis of physical domains coupled with sleep behavioral analysis will offer to physicians and healthcare professionals new ways for implementing the current Decision Support Systems for MS.

The goal of the Use Case on Multiple Sclerosis is to test a machine learning / artificial intelligence algorithm able to predict the risk of developing a relapse in MS.

Relapses are unprovoked and unforeseen temporary worsening of physical and cognitive disability, sometimes causing permanent severe disability.

20 Patients will be equipped with a wearable device that will be able to capture gross motor function and sleep characteristic in people with MS. In parallel, the information provided by the wearable device will be correlated with the already existing data from the electronic Patient Reported Outcome (ePRO) and the electronic Performance Measure (ePM).

In particular, the main outcome of the pilot study will be to evaluate quality of life with the Schedule for the Evaluation of Individual Quality of Life-Direct Weighting (SEIQoL-DW) and EuroQOL-5D (EQ-5D).

Use Case 3

Digitally enhanced rehabilitation treatment monitoring for stroke patients

Key research question

How to improve the capacity to predict functional independence after a stroke (measured according to MRS scale score)?

Despite significant advances in treatment of patients with cardio- and cerebro-vascular risk factors and of patients with acute ischemic cerebro-vascular events, stroke is still one of the leading causes of disability and death worldwide. Follow-up on the cognitive and motor recovery process of stroke patients is an important activity towards ensuring that patients (especially chronic ones) can make steady steps towards recuperating their autonomy and improve their quality of life.

The goal of the Use Case 3 is to develop a set of metrics (based on sensed data) and an accompanying software analysis toolkit (ALAMEDA AI Toolkit) that can extend the monitoring capabilities of neurologists for patients that have suffered from a stroke. The purpose of this extended monitoring is to allow physicians to have a continuous update on the patient recovery process, in between clinical visits. The resulting toolkit also helps neurology experts in adapting and prescribing the correct treatment options and to set up an individualized neuro-rehabilitation programme for patients who suffered a stroke.