Lunch€¦ · Y. Ramadass and A. Chandrakasan, “An efficient piezoelectric energy harvesting...
Transcript of Lunch€¦ · Y. Ramadass and A. Chandrakasan, “An efficient piezoelectric energy harvesting...
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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
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#analyticsx
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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
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#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 .
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
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$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
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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
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Heart disease causes 1 in every 4 deaths- Centers for Disease Control & Prevention
2008-2010
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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
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SStreaming Analytics – Multi-phase Analytics
SAS-generated Insights
Investigative Discovery Streaming Events
Enrichment Analytic BusinessData Models Rules
Streaming Events
SAS In-Memory
Publ
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Subs
crib
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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 (
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Streaming ECG data
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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
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Motif Discovery: sliding window
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MMotif Discovery on ECG
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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
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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
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Methods for Activity DetectionSAS Enterprise Miner Modeling
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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.)
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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
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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
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NNormal Breathing
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WWheezing
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Detecting onset of wheezing
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Running on Streaming Data
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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
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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
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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
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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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Breathable Heat Spreaders
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Breathable Heat Spreaders
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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
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Thank you for your attention!
Contact information
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
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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
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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
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• 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
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• 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
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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
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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)
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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
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Simulation Results with Ideal Components
Vp_unloaded = 3V
Vp_unloaded = 0.4V Vp_unloaded = 0.25V
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54ICSL Lab
Intermediate Inductor Discrete Implementation with Shared Inductor
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PCB Schematic
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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
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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
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Measurement Results - 1
The peak voltage across the source increased from 350 mV to 700 mV thanks
to switching inductor!
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60ICSL Lab
Measurement Results-2
The storage 10 μF capacitor is charged to 800 mV in 5 seconds from an unloaded 350 mV input
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Measurement Results-3
Adding the second beam with in-phase signals increased storage-cap voltage from 800 mV to 1.2 V!
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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
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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
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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.
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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.