lunch€¦ · y. ramadass and a. chandrakasan, “an efficient piezoelectric energy harvesting...

Lunch

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ASSIST Industry Meeting

Thursday January 26, 2017 – Raleigh, NC

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Keynote Address

Dr. Gül Ege, R&D Senior Director, SAS Institute

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Co pyr ight © SAS Inst i tute Inc . A l l r ights reser ved.

How Do We Analyze Healthcare Wearable Data?

Dr. Gul EgeSenior Director R&D, Advanced Analytics

#analyticsx

C op yr i g h t © 2016 , SAS Ins t i t u te Inc . A l l r i g h ts r eser v ed .C op yr i g h t © 2016 , SAS Ins t i t u te Inc . A l l r i g h ts r eser v ed .

Agenda• NCSU-ASSIST & SAS Collaboration• Health IoT business impact• Analytical methods for health and wellness data:

Electrocardiogram Anomalies: Motif discovery Activity and fall detection: Enterprise Miner modelsAsthma detection: Time Frequency Analysis functions


#analyticsx


Healthcare Industry Trends• Population growth especially elderly segment• Top medical spend:

Avoidable and repeat hospitalizationTreating chronic conditions

• Challenges in medication compliance • Increased acceptance of technology


$170 billion to $1.6 trillion / year by 2025

Total across industry verticals: $3.9-11.1 trillion

Continuously monitoring chronic conditionsDiabetes, Asthma, Cardiac problems

$700 billion/year: public health improvement by monitoring air and water quality improvements

Impact of IoT in Health and Wellness


ECG – detecting cardiac malfunctions

Activity detection:Interpreting health dataElderly, remote care

Detection of wheezing on streaming data : asthma attack prevention

Analytical methods applied to health data


Heart disease causes 1 in every 4 deaths- Centers for Disease Control & Prevention

2008-2010

C op yr i g h t © 2016 , SAS Ins t i t u te Inc . A l l r i g h ts r eser v ed .

RabbitMQ

SAS ESP

ECG pads in shirt

Sensor board

Bluetooth Low Energy(BLE)

NCSU Android app w/SAS mods

WiFi

Current Architecture NCSU-ASSIST ECG Shirt


SStreaming Analytics – Multi-phase Analytics

SAS-generated Insights

Investigative Discovery Streaming Events

Enrichment Analytic BusinessData Models Rules

Streaming Events

SAS In-Memory

Publ

ish

Subs

crib

e


SAS® Event Stream ProcessingKey Characteristics

Technology Is the architecture to process steams of data events, on the move, prior to storage, when events happen

SpeedProcesses huge volumes of streaming data flowing at very high rates (Millions of events/sec) with very short latency (


Streaming ECG data


Motif DiscoveryA motif is a repeated pattern in a data sequence

Measure similarity between a target sub-sequence and the input stream

Computationally intensive

Enables early failure warning

Provides anomaly detection based on motif density


Motif Discovery: sliding window


MMotif Discovery on ECG


Interpreting health vitals in light of the activity

Routine elderly care: activity and falls

Classify activity signals

Contextualize ECG signals

Prevent emergencies

Health Wearables: Activity Detection


Methods for Activity Detection X | Y | Z

Max/mean/rangestandard deviation

median absolute deviationdistance between peaks

Energy/entropy

TIME DOMAIN

Feature extraction completed in SAS IML.

max frequency,

,FREQUENCY

DOMAIN


Methods for Activity DetectionSAS Enterprise Miner Modeling


Methods for Activity DetectionEnterprise Miner Modeling

ModelMisclassification Rate

4 activities 12 activities

Neural Network 4.30% 7.69%

Gradient Boosting, PCA 6.58% 12.65%

Decision Tree, Variable Selection 11.35% 30.20%4 activities: sitting, standing, laying, & moving (walking, sit-to-stand, etc.)


Chronic disease with no cure

Inflamed airways: difficulty moving air in and out of the lungs

242million people affected /489K deaths in 2013

Symptoms: coughing, wheezing, shortness of breath

Death and emergency room visits can be minimized by early detection and treatment (inhalers)

Asthma detection on streaming data


Short Time Fourier Transforms

Fourier Transformation with very small moving windows

Used for detection and classification

Capture how the frequency of a signal is changing over time

Vibration & sound data


NNormal Breathing


WWheezing


Detecting onset of wheezing


Running on Streaming Data


Sources of breathing and Wheezing Data Coviello, Jessica S. Auscultation Skills: Breath & Heart Sounds. Lippincott Williams & Wilkins, 2013.

Wrigley, Diane. Heart & Lung Sounds Reference Library. PESI HealthCare, 2011.

Sources of activity data: Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra and Jorge L. Reyes-Ortiz. A Public Domain Dataset for Human Activity Recognition Using Smartphones. 21th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2013. Bruges, Belgium 24-26 April 2013.Bogdan Kwolek, Michal Kepski, Human fall detection on embedded platform using depth maps and wireless accelerometer, Computer Methods and Programs in Biomedicine, Volume 117, Issue 3, December 2014, Pages 489-501, ISSN 0169-2607

Fiber Assemblies for Flexible and Breathable Thermal Conductors Philip Bradford, Associate Professor

Department of Textile Engineering, Chemistry and Science

NC State University

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Thermoelectric devices require maximum heat differential across the device

Transfer of body heat to device is importantCan be accomplished through heat spreader

Transfer of heat away from the device on the environmental side is important

Can be accomplished through heat sink

Major issues for wearable devices For maximum comfort heat spreader should be very flexible and porous to water vapor

For completely flexible TEGs there are no options for flexible heat sinks

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Motivations

CNT Production in My Lab

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C2H2 2C + H2750oC

FeCl2 Catalyst

Growth process based on publication by Inoue et al, Appl. Phys. Lett. (92) 2008

Length-to-diameter ratio of ~ 100,000

This is same as…

…a human hair that is 30 feet long!

… a pencil that is half a mile long!

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Drawable CNT Sheets

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Carbon Nanotube Sheet Take-up

If the mandrel is traversed during takeup, large pieces of fabric are produced

Basis weight is determined by number of layers.

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Carbon Nanotube Fabrics

Based on CNT arrays

Hierarchical porosity

Focus on structural stability, adjusting fiber volume fraction

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Flexible Heat Sinks

5 cm

Carbon post treatment for structural stability

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Flexible Heat Sinks

Bradford et al., Carbon, 2011

Flexbile TEGs often embedded in PDMS

Will explore this material as our structural binder

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Flexible Heat Sinks

CNT sheet – polymer nanofiber hybrid fabrics

Two processes combined to create high strength, conductive nanofiber structures

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Breathable Heat Spreaders

Yildiz et al., Nanoscale, 2015

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Understand structure – thermal property relationships of our materials

Through collaborations with ASSIST members

Integrate these platforms into ASSIST testbeds

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Path Forward

Thank you for your attention!

Contact information

[email protected]

919-515-1866

www.go.ncsu.edu/Bradford

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Q&A

Emerging Research Highlight: Strain Energy and Piezoelectric Harvesting Circuit DesignDr. Mehdi Kiani (Pennsylvania Sate Unviersity

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44ICSL Lab

Integrated Circuits and Systems Lab (ICSL)Electrical Engineering Department, Pennsylvania State University

Efficient Circuit Techniques for Mechanical Energy

Harvesting

January 2017

Miao Meng and Mehdi Kiani

Collaborators: Susan Trolier-McKinstry, Shad Roundy, and Chris Rahn

45ICSL Lab

Multi-Beam Mechanical Wrist/Elbow Harvester

Prof. Susan Trolier-McKinstry

Prof. Shad Roundy

Wrist-worn Harvester

Elbow Joint Harvester

Initial Target: 50 μW from wrist under walking conditions

Target: 2 mW under walking conditions

46ICSL Lab

Creating a prototype of the chest belt harvester using PVDF with parallel electrodes

PVDF

Webbing (also acts as strain limiter)

Soft fabric belt with Teflon OD for low friction

Adjustable buckle for webbing

Aluminum link

Mechanical Chest Harvester

Prof. Chris Rahn

47ICSL Lab

• Design Challenges• Piezoelectric Harvester Equivalent Circuit• Interface Circuit Structures

Standard Interface Circuit

Synchronized Switching Harvesting with Inductor (SSHI)

Intermediate Inductor with Automatic Peak Detection

• Simulations and Measurement Results with Discrete Implementation

Outline

48ICSL Lab

• Decaying sinusoidal with varying envelope mostly below the required voltage across the supercapacitor

• Changing input frequency makes switching techniques hard to implement

Design Challenges

• Ability to harvest energy from multiple (for e.g. 6) beams with unknown phase shifts

• Modularity: Ability to combine different boards, each supporting multiple beams

49ICSL Lab

Piezoelectric-Based Mechanical Harvester Equivalent Circuit Model

The current source provides current proportional to the input vibration amplitude, the current is represented as ip=IPsin pt

Cp represents the plate capacitance of the piezoelectric material

Rp represents the damping loss

Y. Ramadass and A. Chandrakasan, “An efficient piezoelectric energy harvesting interface circuit using a bias-flip rectifier and shared inductor,”IEEE J. Solid-State Circuits, vol. 45, no. 1, pp. 189–204, 2012.

RpCp 45 nF

50ICSL Lab

Standard Energy Harvesting Interface

Full-bridge rectifier and smoothing capacitor, CRECT

When VBR is larger than VRECT + 2VD, the rectifier is conducting (VD: diode turn-on voltage)

Not suitable when the signal has a decaying envelopeY. Ramadass and A. Chandrakasan, “An efficient piezoelectric energy harvesting interface circuit using a bias-flip rectifier and sharedinductor,” IEEE J. Solid-State Circuits, vol. 45, no. 1, pp. 189–204, 2012.

51ICSL Lab

Synchronized Switching Harvesting with Inductor (SSHI)

Y. Ramadass and A. Chandrakasan, “An efficient piezoelectric energy harvesting interface circuit using a bias-flip rectifier and sharedinductor,” IEEE J. Solid-State Circuits, vol. 45, no. 1, pp. 189–204, 2012.

Parallel switch (M1) and inductor (LBF) and a bridge rectifierM1 is briefly turned on when ip changes direction, L flips the voltage of the piezo element (VBF)

52ICSL Lab

Intermediate Inductor Circuit

Two Advantages:

Instead of charging Cp from V+PZT(Pk) to V-PZT(Pk), it charges Cp from 0 to VPZT(PK), saving current from charging Cp

Using L as a current source, the effect of forward voltage across the rectifier can be reduced

53ICSL Lab

Simulation Results with Ideal Components

Vp_unloaded = 3V

Vp_unloaded = 0.4V Vp_unloaded = 0.25V

54ICSL Lab

Intermediate Inductor Discrete Implementation with Shared Inductor

55ICSL Lab

PCB Schematic

56ICSL Lab

PCB Layout and Proof-of-Concept Board

Proof-of-concept board size: 65 mm x 65 mm, including footprints for battery and super-capacitor

57ICSL Lab

Modularity: Combining Two Separate Boards

58ICSL Lab

Simulation Results-Current

During charging capacitor, each individual board generated 44 mAThe combined current of 88 mA was flowing into the storage capacitor

59ICSL Lab

Measurement Results - 1

The peak voltage across the source increased from 350 mV to 700 mV thanks

to switching inductor!

60ICSL Lab

Measurement Results-2

The storage 10 μF capacitor is charged to 800 mV in 5 seconds from an unloaded 350 mV input

61ICSL Lab

Measurement Results-3

Adding the second beam with in-phase signals increased storage-cap voltage from 800 mV to 1.2 V!

62ICSL Lab

• Conventional energy-harvesting interface circuit, SSHIand intermediate inductor were simulated andimplemented with discrete components on PCB

• The intermediate-inductor technique demonstratedoptimal performance in our simulations

• Discrete implementation of the intermediate-inductorcircuit showed promising results

• Intermediate-inductor circuit successfully addressedlow input voltages and changing frequency

• Simulation and measurement results demonstrated theability of combining several boards and charging thesame storage capacitor

Conclusion

63ICSL Lab

Piezo Modeling with Real Device

=_

_ =+

, =1

= × 360 = tan

Measurements were taken for different voltage amplitude and different frequenciesSolve the equations, we get

Rp ~ 1 MCp ~ 45 nF

64ICSL Lab

Half-Wave Intermediate Inductor with Peak Detection Circuits in 0.35 um

CMOS Technology

Half-wave rectification with peak detectionM1 and M2 are on during inductor charging, M3 is on when M1 and M2 are off to let piezo charge itself and inductor charge output at the same time

65ICSL Lab

Simulation Results

Output is charging to 5 V in 500 msSwitching happens at the positive peak of Vp (voltage across piezo)The switching waveforms of M1, M2, and M3 show that the peak detection and switching generation circuits are working well

Output Voltage

Vp

Switching of M1 and M2

Switching of M3

66ICSL Lab

Power Consumption

The power consumption summary of the proposed circuit with frequency of 100 Hz, supplied with 5V, ideal bias current and continuous non-damping signal with an open-circuit amplitude of ~3 V and ~0.35 V

Dynamic PowerStatic Power

Vp,open=3V Vp,open=0.35V

Comparator 32 nW 43 nW 5.3 nWDelay Element 52 nW 53 nW 10 nWWhole Circuit 164 nW 200 nW 15.5 nW

67ICSL Lab

SSHI Discrete Implementation

MCU to generate switch control signals.Zero-crossing detection to detect the first zero-crossing of input signal, then switching is synchronized for constant frequency.Active, passive, and full-bridge rectifier are connected in parallel, the best one from measurement will be used.

68ICSL Lab

SSHI PCB

Board Size: 45 mm x 55 mm.

Battery and super capacitor holders are added.

Battery: coin battery (3V) with diameter of 20 mm.

Super Capacitor: same size as battery.

69ICSL Lab

SSHI Measurement Results

Measurements were made with the designed PCB for and results are compared for conventional full-bridge rectifier and SSHI. As shown in the picture below, for a unloaded Vp of 0.35V, conventional full-bridge could not harvest energy at all, on the other hand, SSHI can harvest energy to charge VSTORE to 0.45 V.

lunch€¦ · y. ramadass and a. chandrakasan, “an efficient piezoelectric energy harvesting...

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