November, 20th 2013

AD-PERSONAS A Cloud Platform for smart-Health services based on

wearable sensors

Raffaele Gravina

Outline

Background

AD-PERSONAS

1. Software Platform

2. Algorithms

3. Case studies

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Smart-Health & Wearable Sensors Wireless Body Sensor Networks (BSNs) are WSN applied to the

human body.

One or often multiple tiny wireless sensor nodes are

Inserted into garments (e.g. smart fabrics), or

Applied directly on the skin (e.g. with electrodes or elastic strap bands)

They have wireless communication capabilities to connect to a personal

mobile coordinator device (e.g. smartphone or tablet)

Applications:

m-Health,

e-Fitness & e-Wellness,

emotion and stress recognition,

smart personal mobility,

interactive gaming, …

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The Project AD-PERSONAS: A Customizable Distributed Platform based

on Body Sensor Networks for Pervasive and Continuous

Monitoring of Assisted Livings

Funding: 2007-2013 NOP for Research and Competitiveness

for the Convergence Regions – Social Innovation Projects

Start Date: November 31st, 2012

Duration: 30 months

Budget: 187.000,00 €

Web Site: http://ad-personas.dimes.unical.it

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AD-PERSONAS It’s a customizable Cloud computing platform to enable smart-Health services,

based on wireless wearable sensing devices, for continuous noninvasive remote

monitoring of assisted livings

Three-Tier,

open-source,

distributed,

Cloud-based

Outcomes Faster software prototyping

More accurate and relevant medical data

Interoperability among services

Higher comfort for patients

Economic impact

High-level architecture

Software architecture

The algorithms Action recognition

Supervised learning

Decisions Trees (e.g. J48)

KNN

Startle reflex and arousal detection

Pattern Recognition

Template Matching (+)

Time warping

Power-efficient

Real-time

Embedded implementation

System configuration:

2 wireless motion sensors

1 personal mobile device

Recognized Activities and posture:

walking, standing, sitting, lying, ...

Energy Expenditure (Kcal)

Accuracy >98%

Case study 1 Physical Activity Recognition

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Full ECG Trace (2 channels, 150Hz)

Heart Rate

Abnormal cardiac activity notification

Mental Stress Detection

Fear and Anxiety recognition

Real-time, 24/7

Low-power

Wearable

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Case study 2 Cardiac Monitoring