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 • 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 WP1: respiratory rate and volume WP2: cardiac output
WP3:
Monitoring system
energy expenditure
WP4:
Flexible optical fibers
Electrical Impedance Tomograohy
NIRS
Anaerobic threshold
blood pressure
WP5:
ICG, ECG, PPG
ECG T-shirt WP6: wireless body sensor network WP7: ECG analysis
Textile based ECG electrodes
Monitoring system WP1: respiratory rate and volume WP2: cardiac output
WP3:
Monitoring system
energy expenditure
WP4:
Flexible optical fibers
Electrical Impedance Tomograohy
NIRS
Anaerobic threshold
blood pressure
WP5:
ICG, ECG, PPG
ECG T-shirt WP6: wireless body sensor network WP7: ECG analysis
Textile based ECG electrodes
Monitoring system • WP1: Monitoring of respiratory rate and volume EMPA - CSEM
Monitoring system WP1: respiratory rate and volume WP2: cardiac output
WP3:
Monitoring system
energy expenditure
WP4:
Flexible optical fibers
Electrical Impedance Tomography
NIRS
Anaerobic threshold
blood pressure
WP5:
ICG, ECG, PPG
ECG T-shirt WP6: wireless body sensor network WP7: ECG analysis
Textile based ECG electrodes
… Monitoring system
• 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 WP1: respiratory rate and volume WP2: cardiac output
WP3:
Monitoring system
energy expenditure
WP4:
Flexible optical fibers
Electrical Impedance Tomography
Oxygen consumption by NIRS
Anaerobic threshold
blood pressure
WP5:
ICG, ECG, PPG
ECG T-shirt WP6: wireless body sensor network WP7: ECG analysis
Textile based ECG electrodes
… 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).
… Monitoring system
• …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.
… Monitoring system
• …Estimation of energy expenditure Fick-based method
USZ
VO2 =
VO2: Oxygen consumption (mL/100g/min), CO: Cardiac output (mL/100g/min), cHb: Haemoglobin concentration (g/dL). CO
stroke volume heart beat, SV = EDV – ESV , SaO2 pulse oximetry, SvO2 novel NIRS system.
measured as part of other WPs
… Monitoring system
• …Estimation of energy expenditure Fick-based method
USZ Energy expenditure
Heart beat Respiration rate
Energy expenditure Heart beat (beats/min)
Stroke volume
Respiration rate
… Monitoring system
• …Estimation of energy expenditure Sensor design and cell-phone/laptop interface
Monitoring system WP1: respiratory rate and volume WP2: cardiac output
WP3:
Monitoring system
energy expenditure
WP4:
Flexible optical fibers
Electrical Impedance Tomography
NIRS
Anaerobic threshold
blood pressure
WP5:
ICG, ECG, PPG
ECG T-shirt WP6: wireless body sensor network WP7: ECG analysis
Textile based ECG electrodes
… 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.
Monitoring system WP1: respiratory rate and volume WP2: cardiac output
WP3:
Monitoring system
energy expenditure
WP4:
Flexible optical fibers
Electrical Impedance Tomography
NIRS
Anaerobic threshold
blood pressure
WP5:
ICG, ECG, PPG
ECG T-shirt WP6: wireless body sensor network WP7: ECG analysis
Textile based ECG electrodes
… Monitoring system
• WP5: Smart ECG T-shirts EMPA - CSEM Textile based ECG electrodes with humidication pad, Integration into T-shirt and short validation.
Monitoring system WP1: respiratory rate and volume WP2: cardiac output
WP3:
Monitoring system
energy expenditure
WP4:
Flexible optical fibers
Electrical Impedance Tomography
NIRS
Anaerobic threshold
blood pressure
WP5:
ICG, ECG, PPG
ECG T-shirt WP6: wireless body sensor network WP7: ECG analysis
Textile based ECG electrodes
‌ Monitoring system
• 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.
Monitoring system WP1: respiratory rate and volume WP2: cardiac output
WP3:
Monitoring system
energy expenditure
WP4:
Flexible optical fibers
Electrical Impedance Tomography
NIRS
Anaerobic threshold
blood pressure
WP5:
ICG, ECG, PPG
ECG T-shirt WP6: wireless body sensor network WP7: ECG analysis
Textile based ECG electrodes
… 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.
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)
Scenario 1: physical activity & lifestyle interventions
• Methodology: Measurement of ventilation by
applying flexible plastic optical fibers, 3-axis accelerometer,
Scenario 2: Hospitalization monitoring
• Methodology Wireless body sensor networks (WBSN). 10 dry ECG electrodes. Accelerometers as ECG quality index. PPG, ICG Beat to beat blood pressure estimation. Microphone cardiovascular autonomic neuropathy (CAN).
Scenario 3: Ambulatory monitoring
• Methodology 10 dry ECG electrodes. Automatic arrhythmia detection
Cardiovascular autonomic neuropathy detection
Accelerometers as ECG quality index. PPG, ICG Beat to beat blood pressure estimation.