Obesense - Nano-Tera 2015

Page 1

ObeSense Monitoring the Consequences of Obesity


Motivations  Obesity is associated with multiple health problems      

Cardiovascular diseases Atrial fibrillation Hypertension Obstructive sleep apnea Diabetes Certain types of cancer

 Has been proven to reduce life expectancy 

10% of premature adult deaths

 Is reaching epidemic proportions 

i. e. Switzerland: 48.7% overweight, 8.3% obese  7.3% of the total healthcare expenses

 Guidelines about identification, evaluation and treatment exist  

Those guidelines require long-term monitoring Such monitoring systems do not exist

2


Objectives

3

 Answer a clear medical need by joining research in physiological markers sensors with clinical end-users  Develop innovative and non-invasive sensors.  Integrate them into single long-term monitoring systems adapted

to obese patients. • Multi-parametric, low-power, allergy-free, comfortable, with online feedback.

 Sophisticated software and algorithms.

 Central involvement of end-users. • Through 3 clinical scenarios


Monitoring system

Monitoring system WP1: respiratory rate and volume

Flexible optical fibers

WP2: cardiac output

Electrical Impedance Tomograohy

WP3: energy expenditure

NIRS

WP4: blood pressure

Anaerobic threshold

WP5: ECG T-shirt

ICG, ECG, PPG

WP6: wireless body sensor network

Textile based ECG electrodes

WP7: ECG analysis

4


Monitoring system

Monitoring system WP1: respiratory rate and volume

Flexible optical fibers

WP2: cardiac output

Electrical Impedance Tomograohy

WP3: energy expenditure

NIRS

WP4: blood pressure

Anaerobic threshold

WP5: ECG T-shirt

ICG, ECG, PPG

WP6: wireless body sensor network

Textile based ECG electrodes

WP7: ECG analysis

5


Monitoring system  WP1: Monitoring of respiratory rate and volume EMPA - CSEM

7


Monitoring system

Monitoring system WP1: respiratory rate and volume

Flexible optical fibers

WP2: cardiac output

Electrical Impedance Tomography

WP3: energy expenditure

NIRS

WP4: blood pressure

Anaerobic threshold

WP5: ECG T-shirt

ICG, ECG, PPG

WP6: wireless body sensor network

Textile based ECG electrodes

WP7: ECG analysis

8


… Monitoring system

9

 WP2: Cardiac output CSEM – EPFL/LTS5 – EPFL/LHTC feasibility of measuring cardiac output non-invasively via electrical impedance tomography (EIT)

EIT

CO = 5 l/min


1. Simulations

‌ Monitoring system

2. Measurements

4D Bio-Impedance Model

EIT In planning‌


Monitoring system

Monitoring system WP1: respiratory rate and volume

Flexible optical fibers

WP2: cardiac output

Electrical Impedance Tomography

WP3: energy expenditure

Oxygen consumption by NIRS

WP4: blood pressure

Anaerobic threshold

WP5: ECG T-shirt

ICG, ECG, PPG

WP6: wireless body sensor network

Textile based ECG electrodes

WP7: ECG analysis

11


… Monitoring system

 WP3: Estimation of energy expenditure  Detection of anaerobic threshold (AT)

IRR, CSEM, EPFL-ASPG Respiratory variables recorded from 12 healthy subjects while exercising incrementally. BR and VT by ergospirometer, HR by instrumented t-shirt (CSEM SEW model).

12


… Monitoring system

13

 …Estimation of energy expenditure  Platform with 3D accelerometer and ECG front-end almost complete

Front view

Front view with electronic components Back view


‌ Monitoring system

Energy expenditure estimation based on acceleration and ECG compared to indirect calorimetry.

14


‌ Monitoring system

15

 ‌Estimation of energy expenditure  Fick-based method

USZ

VO2: CO: cHb: CO SaO2 SvO2

VO2 =

đ?‘?đ??ťđ?‘?Ă—coĂ—

SaO2 – SvO2 đ?‘˜1

Oxygen consumption (mL/100g/min), Cardiac output (mL/100g/min), Haemoglobin concentration (g/dL). stroke volume Ă— heart beat, SV = EDV – ESV ≈ 70 đ?‘šđ??ż, pulse oximetry, novel NIRS system.

measured as part of other WPs


… Monitoring system

16

 …Estimation of energy expenditure  Fick-based method

USZ Energy expenditure

Heart beat

Respiration rate

Energy expenditure

Heart beat (beats/min) Respiration rate

Stroke volume


… Monitoring system

 …Estimation of energy expenditure  Sensor design and cell-phone/laptop interface

17


Monitoring system

Monitoring system WP1: respiratory rate and volume

Flexible optical fibers

WP2: cardiac output

Electrical Impedance Tomography

WP3: energy expenditure

NIRS

WP4: blood pressure

Anaerobic threshold

WP5: ECG T-shirt

ICG, ECG, PPG

WP6: wireless body sensor network

Textile based ECG electrodes

WP7: ECG analysis

18


… Monitoring system

 WP4: Blood pressure (BP) CSEM Estimation of BP based on Pulse Transit Time (PTT). Non-invasive, continuous measurement based on ICG, ECG, PPG.

19


Monitoring system

Monitoring system WP1: respiratory rate and volume

Flexible optical fibers

WP2: cardiac output

Electrical Impedance Tomography

WP3: energy expenditure

NIRS

WP4: blood pressure

Anaerobic threshold

WP5: ECG T-shirt

ICG, ECG, PPG

WP6: wireless body sensor network

Textile based ECG electrodes

WP7: ECG analysis

20


… Monitoring system

 WP5: Smart ECG T-shirts EMPA - CSEM  Textile based ECG electrodes with humidication pad,  Integration into T-shirt and short validation.

21


Monitoring system

Monitoring system WP1: respiratory rate and volume

Flexible optical fibers

WP2: cardiac output

Electrical Impedance Tomography

WP3: energy expenditure

NIRS

WP4: blood pressure

Anaerobic threshold

WP5: ECG T-shirt

ICG, ECG, PPG

WP6: wireless body sensor network

Textile based ECG electrodes

WP7: ECG analysis

22


‌ Monitoring system

23

 Wireless body sensor network CSEM Embedded architecture for processing of multiple bio-signals and the integration of signal processing algorithms on the embedded hardware.


… Monitoring system

 Multi-parameter sensing EPFL - ESL Touch based/wearable:  1-lead ECG  Respiration  Skin conductance  Motion  Body fat and hydration level  Emotions: mood (valence/arousal), stress  Real time BT 4.0 communication, open APIs.

24


Monitoring system

Monitoring system WP1: respiratory rate and volume

Flexible optical fibers

WP2: cardiac output

Electrical Impedance Tomography

WP3: energy expenditure

NIRS

WP4: blood pressure

Anaerobic threshold

WP5: ECG T-shirt

ICG, ECG, PPG

WP6: wireless body sensor network

Textile based ECG electrodes

WP7: ECG analysis

25


… Monitoring system

 ECG analysis EPFL - ASPG  QRS complexes and fiducial points detection in the ECG by

means of mathematical morphology operators in an adaptive manner.

26


Clinical scenarios  Scenario 1: physical activity & lifestyle interventions – Supervised by Dr O. Dériaz (IRR) and Dr U. Mäder

(SFISM) on patients following activity regimen in lab settings and at home

 Scenario 2: hospitalization monitoring – Obesity and atrial fibrillation, hypertension and type-

2 diabetes – Supervised by Dr E. Pruvot (CHUV)

 Scenario 3: ambulatory monitoring – Obesity and outpatient cardiovascular complications – Supervised by Dr E. Pruvot (CHUV)

27


Turn static files into dynamic content formats.

Create a flipbook
Issuu converts static files into: digital portfolios, online yearbooks, online catalogs, digital photo albums and more. Sign up and create your flipbook.