Matteo Pastorino

A comprehensive motor symptom monitoring and management system: The bradykinesia case

The current work describes a methodology to automatically detect the severity of bradykinesia in motor disease patients using wireless, wearable accelerometers. This methodology was tested with cross validation through a sample of 20 Parkinsons disease patients. The assessment of methodology was carried out through some daily living activities which were detected using an activity recognition algorithm. The Unified Parkinsons Disease Rating Scale (UPDRS) severity classification of the algorithm coincides between 70 and 86% from that of a trained neurologist depending on the classifier used. These severities were calculated for 5 second segments of the signal with 50% of overlap. A bradykinesia profiler is also presented in this work. This profiler removes the overlap of the segments and calculates the confidence of the resulting events. It also calculates average severity, duration and symmetry values for those events. The profiler has been tested with a bogus dataset. Future work includes better training for the severity classifier with a larger sample and testing the profiler with real, longterm patient data in a projected pilot phase in three European hospitals.

Wearability assessment of a wearable system for Parkinson's disease remote monitoring based on a body area network of sensors.

Wearable technologies for health monitoring have become a reality in the last few years. So far, most research studies have focused on assessments of the technical performance of these systems, as well as the validation of the clinical outcomes. Nevertheless, the success in the acceptance of these solutions depends not only on the technical and clinical effectiveness, but on the final user acceptance. In this work the compliance of a telehealth system for the remote monitoring of Parkinsons disease (PD) patients is presented with testing in 32 PD patients. This system, called PERFORM, is based on a Body Area Network (BAN) of sensors which has already been validated both from the technical and clinical point for view. Diverse methodologies (REBA, Borg and CRS scales in combination with a body map) are employed to study the comfort, biomechanical and physiological effects of the system. The test results allow us to conclude that the acceptance of this system is satisfactory with all the levels of effect on each component scoring in the lowest ranges. This study also provided useful insights and guidelines to lead to redesign of the system to improve patient compliance.

Gait assessment in Parkinson's disease patients through a network of wearable accelerometers in unsupervised environments

Parkinsons disease (PD) predominantly alters the motor performance of the affected individuals. In particular, the loss of dopaminergic neurons compromises the speed, the automaticity and fluidity of movements. As the disease evolves, PD patients motion becomes slower and tremoric and the response to medication fluctuates along the day. In addition, the presence of involuntary movements deteriorates voluntary movement in advanced state of the disease. These changes in the motion can be detected by studying the variation of the signals recorded by accelerometers attached in the limbs and belt of the patients. The analysis of the most significant changes in these signals make possible to build an individualized motor profile of the disease, allowing doctors to personalize the medication intakes and consequently improving the response of the patient to the treatment. Several works have been done in a laboratory and supervised environments providing solid results; this work focused on the design of unsupervised method for the assessment of gait in PD patients. The development of a reliable quantitative tool for long-term monitoring of PD symptoms would allow the accurate detection of the clinical status during the different PD stages and the evaluation of motor complications. Besides, it would be very useful both for routine clinical care as well as for novel therapies testing.

Assessment of bradykinesia in Parkinson's disease patients through a multi-parametric system

The aim of this paper is to describe and present the results of the automatic detection and assessment of bradykinesia in motor disease patients using wireless, wearable accelerometers. The current work is related to a module of the PERFORM system, a FP7 project from the European Commission, that aims at providing an innovative and reliable tool, able to evaluate, monitor and manage patients suffering from Parkinsons disease. The assessment procedure was carried out through a developed C# library that detects the activities of the patient using an activity recognition algorithm and classifies the data using a Support Vector Machine trained with data coming from previous test phases. The accuracy between the output of the automatic detection and the evaluation of the clinician both expressed with the Unified Parkinsons disease Rating Scale, presents an average value of [68.3±8.9]%. A meta-analysis algorithm is used in order to improve the accuracy to an average value of [74.4±14.9]%. Future work will include a personalized training of the classifiers in order to achieve a higher level of accuracy.

Wearable sensor network for health monitoring: the case of Parkinson disease

The aim of this paper is to show how wearable sensors can be useful in health solutions, improving the continuous monitoring and management of patients. This paper is focused on the available solution for motion analysis, providing a description of human motion features which can be measured through the use of wearable sensors. Moreover, this paper presents an example of wearable solution used for the objective assessment of Parkinsons disease symptoms. Results indicate that wearable sensors are useful for the objective evaluation of motor fluctuation and clinicians can benefit from these tools in order to adjust and personalise the treatment.

Using Human-Computer Interface for Rehabilitation of Activities of Daily Living (ADL) in Stroke Patients: Lessons from the First Prototype

Technological progress in the area of health informatics provides new prospects for the neurorehablitation of neurological patients. The CogWatch project (www.cogwatch.eu) is dedicated to development of automatized assistance system to improve motor planning and task execution for stroke survivors, who suffer from Apraxia and Action Disorganization Syndrome (AADS). The system is targeted at promoting user independence from the therapist or care-provider during performance of Activities of Daily Living (ADL). In this study, we present insights from the evaluation of the first prototype interface, designed to aid users with hot drink preparation in the kitchen environment (i.e. tea-making). Ten out of the eleven tested participants (8 patients; 3 controls) were able to prepare the selected cup of tea using the Cogwatch System. A case studies summary is presented to illustrate a successful example of patient-computer interactions and a proof of concept.

Mobile Systems as a Challenge for Neurological Diseases Management – The Case of Parkinson's Disease

Nowadays the importance of bio-medical engineering and mobile applications for healthcare is amazingly growing. During the last decades many devices and technological solutions have become available on the market and the interest in applying those technologies to the treatment of several kinds of pathologies has consequently increased. This chapter addresses the problem of continuous monitoring of patients affected by Parkinson’s Disease (PD) and proposes a set of technologies to improve the following and management of such subjects. PD is a neurodegenerative disorder of the central nervous system that affects motor skills and speech (Tolosa, 1998). The primary biochemical abnormality in PD is a deficiency of dopamine due to degeneration of neurons in the substantia nigra pars compact (D. G. Standaert & Young, 2001). The characteristic motor features of the disease include bradykinesia (i.e. slowness of movement), tremor, rigidity (i.e. resistance to externally imposed movements), flexed posture, postural instability and freezing of gait. Furthermore, PD is usually characterised by the loss of normal prosody of the speech (Darkins et al., 1988). According to the World Health Organisation [WHO], 2002), there are more than six million people worldwide affected by PD. The syndrome typically appears around the age of 60. It affects Europeans and North Americans more often than Asians or Africans and it is more common in men than in women. PD affects about 2% of the population over the age of 65 years, figure that is expected to double by 2020 (de Lau & Breteler, 2006). For those reasons, PD poses a significant public health burden, which is likely to increase in the coming years. Annual medical care, including doctors’ visits, physical therapies and treatment for cooccurring illnesses -such as depressionis estimated at

State of the Art on Games for Health Focus on Parkinson’s Disease Rehabilitation

2,000 to

Hierarchy Definition for the Evaluation of a Telehealth System for Parkinson’s Disease Management

7,000 for people in early stages of the disease, and it is probably much higher for advanced stages. Surgical treatments for PD can cost

A mobile monitoring tool for the automatic activity recognition and its application for Parkinson’s disease rehabilitation

25,000 or more. As the disease progresses, institutional care at an assisted-living facility or nursing home may be required, and the related costs can exceed