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NEurobehavioural predictiVE and peRsonalised Modelling of depressIve symptoms duriNg primary somatic Diseases with ICT-enabled self-management procedures

Periodic Reporting for period 1 - NEVERMIND (NEurobehavioural predictiVE and peRsonalised Modelling of depressIve symptoms duriNg primary somatic Diseases with ICT-enabled self-management procedures)

Reporting period: 2016-01-01 to 2017-06-30

Personal health systems for the management of chronic diseases have seen giant leaps in development over recent years. These systems offer vital sign monitoring and therapy delivery at home, focusing on the primary physical disease conditions. However, they do not provide support for early mood assessment or psychological treatment and lack a real-time comprehensive assessment of the patient’s mental status.
Depression is the third leading contributor to global diseases, and depressive mood state is also considered to be strictly related to the onset or worsening of a severe primary somatic disease. Indeed effective preventive medicine related to the onset of depressive symptoms as a comorbidity and worsening factor of psychosomatic diseases such as myocardial infarction, leg-amputation, cancer, and kidney failure is lacking.
NEVERMIND sets out to empower people who suffer from symptoms of depression related to a serious somatic disease by placing them at the center of their mental healthcare. Equipped with just a smartphone and a lightweight sensitized shirt, patients seeking care and treatment for their mental illnesses interact with these devices that collect data about their mental and physical health, to then get effective feedback.
Lifestyle factors, i.e. diet, physical activity and sleep hygiene, play a significant mediating role in the development, progression and treatment of depression, and in NEVERMIND will be monitored by a real-time Decision Support System running locally on the patient’s smartphone, predicting the severity and onset of depressive symptoms, by processing physiological data, body movement, speech, and the recurrence of social interactions. The data will trigger a response encouraging the patient to conduct or alter activities or lifestyle to reduce the occurrence and severity of depressive symptoms.
The final aim is to bring this system to the market, giving people the tools to control their depression and unburden their minds.
The main objective in the first period of the project was to design, develop, and set-up the whole NEVERMIND platform, including in-app services and remote database and processing facilities.
To this end, recommendations were collected from patients involved in the study, clinicians, literature research, relatives, carers, possible stakeholders and representatives of care authorities. Clinical partners carried out an investigation on depressive symptoms as a comorbidity factor in severe somatic conditions from the literature in order to establish an updated state of the art of risk stratification of depressive symptoms in the pathological conditions and determine specific features and parameters that can be critical to be implemented in the NEVERMIND platform, also considering patient personalization according to each somatic disorder. In this investigation, the most salient points for personalization of the NEVERMIND platform were exploited, such as: a) latency between onset of medical condition and onset of depression; b) typical degree of functional impairment associated with the somatic disease; c) typical degree of burden of relatives/carers; d) identification of useful cognitive mood and emotional tests. Results from this task constituted a set of clinical requirements and physiological constraints to be implemented in the NEVERMIND system, and to be tested during a 9-month pilot study. These results fed into the definition of scientific, technical, and clinical requirements for the definition of self-management and intervention procedures in the case of comorbid depressive symptoms, which will be used to tune the real-time DSS and the user interface.
Fostered personalised plan of care will be based on: a) the initial assessment; b) the feedback received from the smartphone/tablet on life style indications; c) the feedback from the smart shirt sensors: sleep quality, levels of arousal, correct breathing and mindfulness practice; d) physical activity; e) identify specific self-managing activities to be performed by patients while using the system.
In parallel, work was done to develop and integrate the wearable hardware system for the NEVERMIND platform. Specifically, the NEVERMIND wearable monitoring platform is comprised of a portable data logger, a set of garments, and additional base station serving also as a recharging dock. A set of garments was tailored to males and females in personalized sizes, embedded with textile sensors, i.e. ECG electrodes and respiration piezoresistive sensors.
A real-time DSS module running on the user’s smartphone and making predictions about the patient’s depressive symptoms was extended and tailored to the existing prediction models. Moreover, the implementation of the DSS updater module, a web service provider representing the computational workhorse of the whole NEVERMIND system was developed. A web server, implemented using CherryPy, will take new data and will spawn new processing threads to update the real-time DSS prediction algorithms.
The design, integration and development of the user interface, and background ICT solutions for clinicians and patients was performed. The interface will be tailored using the specifications from the clinicians, and a mindfulness-specific module was developed together with other intervention tools supporting patients’ self management of the disease. This was all integrated with the DSS server and Deprexis software.
Techniques and specific rules meaningful for the implementation of self-management procedures of depressive symptoms were defined. Specifically, patient-specific feedback was defined according to the patient's primary disease, lifestyle, and personal emotional style. Accordingly, e-mindfulness procedures were tailored to the patient needs and, if needed, will be administered to them.
Development guidelines were developed for the NEVERMIND platform for successful integration within the healthcare and social systems and other ta
A novel integrated system able to record and process physiological signals, together with psychometric scores, to predict depressive symptoms in case of severe somatic diseases has been developed. Effective intervention tools including state-of-the-art lifestyle advices, as well as meditation and behavioral and psychological therapies have been implemented as well.
The consortium is now able to run a randomized clinical trial to compare the effects when using the Nevermind system with treatment as usual.
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