Manuel Ottaviano

Smartphone Application for the Analysis of Prosodic Features in Running Speech with a Focus on Bipolar Disorders: System Performance Evaluation and Case Study

Bipolar disorder is one of the most common mood disorders characterized by large and invalidating mood swings. Several projects focus on the development of decision support systems that monitor and advise patients, as well as clinicians. Voice monitoring and speech signal analysis can be exploited to reach this goal. In this study, an Android application was designed for analyzing running speech using a smartphone device. The application can record audio samples and estimate speech fundamental frequency, F0, and its changes. F0-related features are estimated locally on the smartphone, with some advantages with respect to remote processing approaches in terms of privacy protection and reduced upload costs. The raw features can be sent to a central server and further processed. The quality of the audio recordings, algorithm reliability and performance of the overall system were evaluated in terms of voiced segment detection and features estimation. The results demonstrate that mean F0 from each voiced segment can be reliably estimated, thus describing prosodic features across the speech sample. Instead, features related to F0 variability within each voiced segment performed poorly. A case study performed on a bipolar patient is presented.

Heart Failure Monitoring System Based on Wearable and Information Technologies

Cardiovascular diseases (CVD) are the leading source of death in the western world and in particular, in Europe CVD cause 45% of all deaths. Besides, heart failure (HF), the paradigm of CVD, affects mainly people older than 65. Facing this reality, the European Union funded MyHeart Project, whose mission is empowering citizens to fight CVD by means of a preventive lifestyle and an early diagnosis. This paper presents an innovative integrated solution for the assessment of heart failure: HF management (HFM). HFM is a heart failure disease management system that makes use of innovative approaches, based on information technologies (IT) and wearable technologies, for the continuous assessment of HF progression and cardiovascular risk stratification. By integrating patient data from different sources with special emphasis in the information obtained from extensive ECG processing the system assesses the patients cardiac condition. Rather than just merely evaluating the cardiovascular status, HFM is designed to motivate patients to acquire an active role in their health management and to help them to improve their cardiac condition by promoting physical exercise

A dashboard-based system for supporting diabetes care

Objective To describe the development, as part of the European Union MOSAIC (Models and Simulation Techniques for Discovering Diabetes Influence Factors) project, of a dashboard-based system for the management of type 2 diabetes and assess its impact on clinical practice. Methods The MOSAIC dashboard system is based on predictive modeling, longitudinal data analytics, and the reuse and integration of data from hospitals and public health repositories. Data are merged into an i2b2 data warehouse, which feeds a set of advanced temporal analytic models, including temporal abstractions, care-flow mining, drug exposure pattern detection, and risk-prediction models for type 2 diabetes complications. The dashboard has 2 components, designed for (1) clinical decision support during follow-up consultations and (2) outcome assessment on populations of interest. To assess the impact of the clinical decision support component, a pre-post study was conducted considering visit duration, number of screening examinations, and lifestyle interventions. A pilot sample of 700 Italian patients was investigated. Judgments on the outcome assessment component were obtained via focus groups with clinicians and health care managers. Results The use of the decision support component in clinical activities produced a reduction in visit duration (P ≪ .01) and an increase in the number of screening exams for complications (P < .01). We also observed a relevant, although nonstatistically significant, increase in the proportion of patients receiving lifestyle interventions (from 69% to 77%). Regarding the outcome assessment component, focus groups highlighted the systems capability of identifying and understanding the characteristics of patient subgroups treated at the center. Conclusion Our study demonstrates that decision support tools based on the integration of multiple-source data and visual and predictive analytics do improve the management of a chronic disease such as type 2 diabetes by enacting a successful implementation of the learning health care system cycle.

A system to promote self-behaviors of patients with coronary heart disease

Personalized health devices are the novel paradigm to reduce healthcare costs and to improve the quality of health services. At the same time, health interventions and promotion of self behaviors generate benefits to healthcare and allow citizens to be more involved in their own health management. This paper describes the process followed in HeartCycle project to design education and coaching services to promote self-behaviors in a closed loop monitoring system for patients with coronary heart diseases that suffered a myocardial infarction.

An m-Health system for education and motivation in cardiac rehabilitation: the experience of HeartCycle guided exercise:

Introduction Home-based programmes for cardiac rehabilitation play a key role in the recovery of patients with coronary artery disease. However, their necessary educational and motivational components have been rarely implemented with the help of modern mobile technologies. We developed a mobile health system designed for motivating patients to adhere to their rehabilitation programme by providing exercise monitoring, guidance, motivational feedback, and educational content. Methods Our multi-disciplinary approach is based on mapping “desired behaviours” into specific system’s specifications, borrowing concepts from Fogg’s Persuasive Systems Design principles. A randomised controlled trial was conducted to compare mobile-based rehabilitation (55 patients) versus standard care (63 patients). Results Some technical issues related to connectivity, usability and exercise sessions interrupted by safety algorithms affected the trial. For those who completed the rehabilitation (19 of 55), results show high levels of both user acceptance and perceived usefulness. Adherence in terms of started exercise sessions was high, but not in terms of total time of performed exercise or drop-outs. Educational level about heart-related health improved more in the intervention group than the control. Exercise habits at 6 months follow-up also improved, although without statistical significance. Discussion Results indicate that the adopted design methodology is promising for creating applications that help improve education and foster better exercise habits, but further studies would be needed to confirm these indications.

A platform for the development of patient applications in the domain of personalized health

Personalized health (p-health) systems can contribute significantly to the sustainability of healthcare systems, though their feasibility is yet to be proven. One of the problems related to their development is the lack of well-established development tools for this domain. As the p-health paradigm is focused on patient self-management, big challenges arise around the design and implementation of patient systems. This paper presents a reference platform created for the development of these applications, and shows the advantages of its adoption in a complex project dealing with cardio-vascular diseases.

Results of the usability and acceptance evaluation of a cardiac rehabilitation system

Cardiac rehabilitation programs are extremely important during the recovery phase of patients who suffered a Myocardial Infarction (MI). Traditionally, these programs aimed at recovering the cardiovascular functioning by means of tailored exercise programs. However, during the last years, researchers and practitioners have started to consider a multi disciplinary approach for the interventions, where patient education and health behaviors changes play a central role both in rehabilitation and in secondary prevention. Nevertheless, the lack of resources and the need to have health professionals continuously involved in the patient supervision process, does not make possible to extend rehabilitation programs to all potential patients in the health care system. This paper presents the results of the usability and acceptance validation of a personalized home based cardiac rehabilitation system developed under the framework of HeartCycle, a project partially funded by the European Commission.

Innovative self management system for guided cardiac rehabilitation

This paper describes the design and development of a system for cardio rehabilitation of patients that suffered a myocardial infarction. The proposed solution focuses on exercise prescriptions and the encouragement of healthy behaviors. The innovative strategy of the design takes into account health promotion models to provide safe, assistive exercise training sessions, personalized feedbacks, and educational contents.

Parametric Cognitive Modeling of Information and Computer Technology Usage by People with Aging- and Disability-Derived Functional Impairments

Despite the speedy evolution of Information and Computer Technology (ICT), and the growing recognition of the importance of the concept of universal design in all domains of daily living, mainstream ICT-based product designers and developers still work without any truly structured tools, guidance or support to effectively adapt their products and services to users’ real needs. This paper presents the approach used to define and evaluate parametric cognitive models that describe interaction and usage of ICT by people with aging- and disability-derived functional impairments. A multisensorial training platform was used to train, based on real user measurements in real conditions, the virtual parameterized user models that act as subjects of the test-bed during all stages of simulated disabilities-friendly ICT-based products design. An analytical study was carried out to identify the relevant cognitive functions involved, together with their corresponding parameters as related to aging- and disability-derived functional impairments. Evaluation of the final cognitive virtual user models in a real application has confirmed that the use of these models produce concrete valuable benefits to the design and testing process of accessible ICT-based applications and services. Parameterization of cognitive virtual user models allows incorporating cognitive and perceptual aspects during the design process.

Patient interaction in homecare systems to treat cardiovascular diseases in the long term

The rapid aging of the population worldwide will dramatically increase the number of people affected by chronic diseases in the next years. This social situation makes it necessary a paradigm shift from reactive care to preventive care. New technological paradigms, like Ambient Intelligence and Ubiquitous Computing, allow the development of Personal Health Systems (PHS) that guarantee the continuity of care and a better use of health resources. Therefore, patients should become the centre of the health care process, and PHS should be designed to fulfill the patients goals and needs. User-centred methodologies provide a good framework for designing general use applications, but they do not usually take into account factors like the context where the interaction is taking place or the medical, social and business contexts that surround the patient. This paper presents a model for designing users interaction in medical applications. The final goal is to develop highly usable user interfaces and to improve the user experience, aiming to guarantee the patients adherence to the medical protocols and recommendations.