Docstoc

Smart and Aware Pervasive Healthcare Environment

Document Sample
Smart and Aware Pervasive Healthcare Environment Powered By Docstoc
					                           SAPHE
    Smart and Aware Pervasive Healthcare
               Environment


                                                             Supported by DTI Technology Programme
www.saphe.info




                 Guang-Zhong Yang, Imperial College London
Technical Objectives
•   Miniaturised sensing with self-management and configuration

•   Local data abstraction and sensor fusion/inferencing with low
    power sensor and wireless data path

•   Processing-on-node technology for context aware sensing

•   Automated trust-based decision support and "affective
    computing" for improved human-computer interfacing

•   Intelligent trend analysis and large scale data mining
Project Overview
•   To develop a novel architecture for unobtrusive pervasive
    sensing to link physiological/metabolic parameters and lifestyle
    patterns for improved well-being monitoring and early detection
    of changes in disease.



             By sensing under normal physiological conditions
             combined with intelligent trend analysis, SAPHE opens
             up new opportunities for the UK ICT and healthcare
             sectors in meeting the challenges of demographic
             changes associated with the aging population


                                                 DTI Technology Programme
                                      Evolution of Computer Technologies
                                                                             Moore's Law
                                                                                                                  Estimate         Actual
                                                                                                                                     Pentium D
                        9
                                                                                                                          P4 Prescott
                        8
                                                                                                                                     Pentium M
                                                                                                                                 Pentium 4
                        7

                                                                                                             Pentium III
                                                                                                  Pentium Pentium II
                        6
    Transistors (log)




                        5
                                                                       80386         80486

                        4
                                                         80286
                             4004 8008         8086
                               8008 8080
                             4-bit 108kHz 8080
                                                                        80386                    Pentium      Pentium II
                                                      8086              32-bit                   32-bit       233MHz      Pentium D
                        3    108kHz
                            4004    8-bit                      80286    20MHz                                       Pentium III
                                            8-bit     16-bit                       80486         66MHz        300MIPS     3.2 GHz
                                                                                                                          P4 Prescott
                                    16kB
                             0.06MIPS                          16-bit   6MIPS                                       450-500MHz M
                                                                                                                           Pentium
                                                                                                              7.5M transistors
                                            2Mhz      8MHz                         25MHz         100MIPS                  15GIPS
                                                                                                                          2.8-3.4 GHz
                                                               12MHz    275K transistors                                 Pentium 4
                                                                                                                    510MIPS600Mhz-1.6GHz
                                    0.06MIPS
                             2.3K transistors                                      20MIPS                     1997
                                                                                                 3.2M transistors         230M
                                                                                                                          125M transistors
                        2
                                            0.64MIPS0.8MIPS 2.7MIPS 1985                                                 1.4&1.5GHz
                                                                                                                    9.5M transistors
                                                                                                                           6.5GIPS
                             1971 3.5K transistors 29K transistors transistors     1.2M transistors
                                                                                                 1993                     2005
                                                                                                                          7GIPS
                                            6k transistors     134K
                                                                                   1989
                                                                                                                         1.7GIPS
                                                                                                                    1999 77M transistors
                                                                                                                          2004
                        1           1972    1974      1978     1982                                                      42M transistors
                                                                                                                           2003
                                                                                                                         2000

                        0
                            1971           1976            1981            1986            1991                 1996                  2003
                                                                              Year
http://velox.stanford.edu/group/chips_micropro_body.html                                           http://www.pc-erfahrung.de/
 http://www.theregister.co.uk/2004/02/02/intel_prescott_90nm_pentium/                              http://www.granneman.com/
http://www.intel.com/products/processor/pentiumm/image.htm                                         http://home.datacomm.ch/fmeyer/cpu/
http://www.pc-erfahrung.de/Index.html?ProzessormodelleIntelItanium2.html                           http://trillian.randomstuff.org.uk/~stephen/history
                                    Evolution of Computer Technologies
Bell’s Law

     New computing class every decade
     New applications and contents develop around each new class
  log (people per computer/price)




                                                   year
Mote Evolution
                                      Biosensor
What does BSN Cover?                   Design


                       Standards &                 Biocompatibility
                        Integration                  & Materials



                                         BSN



                        Autonomic                    Wireless
                         Sensing                   Communication


                                      Low Power
                                       Design &
                                      Scavenging
                 Biosensor Design

Thermistor               Thermistor
                         (ACR system)


ECG                                            Implant ECG recorder
                                               (Medtronics –Reveal)
SpO2
                     Oxymeter
Glucose              (Advanced Micronics)

concentration
                                                               Glucose sensor
                                                               (Glucowatch)
Blood pressure
                           Implant blood pressure
                           flow sensor (CardioMEMS)
pH measurement
                                Implant pH sensor
                                (Metronics – Bravo)


Capsule endoscopy          Pill-sized camera
                           (Given Imaging)
 MEMS - Microelectromechanical System

Integrated micro devices or systems combining
electrical and mechanical components

                                                   Tactile Sensor for Endoscopic Surgery
                                                                   (SFU)
Fabricated using integrated circuit (IC) batch
processing techniques


Size range from micrometers to millimetres
                                                    Pressure Sensor for Clinical Use
                                                                (SFU)
Applications includes: accelerometers, pressure,
chemical and flow sensors, micro-optics, optical
scanners, and fluid pumps

                                                   CMOS Micromachined Flow Sensor
                                                              (SFU)
            Biocompatibility and Materials

                             Implant blood pressure
Biosensors                   flow sensor (CardioMEMS)


                                                 Drug releasing stents -
Stents                                           Taxus stents - Boston Scientific Co.




Tissue Engineering

   Pattern and manipulate cells
   in micro-array format                                            Ozkan et. al (2003), Langmuir




Drug delivery
systems


                     Smart Pill – Sun-Sentinel Co.



                                         Carol Ezzell Webb, “Chip Shots”, IEEE Spectrum Oct 2004
                                  Power Scavenging

Photovoltaics (Solar cells)                                                    Panasonic BP-243318

     15-20% efficiency (single crystal silicon solar cell)
     15mW/cm2 (midday outdoor) to 10µW/cm2 (indoors)
Temperature Gradients

     1.6% efficiency (at 5oC above room temperature)
     40 µW/cm2 (5oC differential, 0.5cm2, and 1V output)
                                                                   Applied Digital Solutions –
Human Power                                                        thermoelectric generator

     Human body burns 10.5MJ/day (average power dissipation of 121W)
     330 µW/cm2 (piezoelectric shoe)
Wind/Air Flow                                                                                      MIT Media Lab

     20-40% efficiency (windmills, with wind velocity 18mph)
Vibrations

     Electromagnetic, electrostatic, and piezoelectric devices
     200 µW (1cm3 power converter with vibration of 2.25 m/s2 at 120Hz)                  MIT – MEMS piezoelectric generator

Nuclear microbatteries

     With 10 milligrams of polonium-210, it can produce 50mW for more than 4 months
     It can safely be contained by simple plastic package, as Nickel-63 or tritium can
                                                                                  Cornell University - Nuclear micro-generator
     penetrate no more than 25 mm
                                                                                   (with a processor and a photo sensor)
         Environment                      Trust,
         Sensors and                     Security
           Context                      and Policy




                                             Self-configuration,
Multi-sensor
                                                  healing,
 Analysis
                                                managing of
and Fusion
                                            software components


                          Network
                          Storage
                        and Decision
                       Support Agents
              Genetic            DNA         Developing                       First                             Progressing
           Predisposition       mutation Molecular signature                symptoms                              disease
Today



                                                                        Diagnosis &        Treatment &
                                                     Screening                                                    Follow-up
                                                                          Staging           Monitoring

                                                   Unspecific markers   Diagnostic imaging Surgery             Diagnostic imaging
                                                   POC imaging          Biopsies           Cath lab            Unspecific marker
                                                   Mammography                             Radiation therapy
Tomorrow




                               Diagnosis &          Treatment &
             Screening                                                      Follow-up
                                 Staging             Monitoring

           Specific markers Molecular imaging       Min invasive surgery    Non-invasive and
           (MDx)            Quantitative imaging    Local/targeted drug     quantitative imaging
                            Whole-body imaging      Delivery                Molecular imaging
                            Comp Aided Diagn.       Drug tracking           Molecular diagnostics (MDx)
                                                    Tissue analysis (MDx)
        Driver 1: The Aging Population

The proportion of elderly people is likely to double from 10% to
20% over the next 50 years.

In the western world, the ratio of workers to retirees is declining.

The number of people living alone is rising.

A change of care provision is needed for these patients.
           Driver 2: Chronic Disease

Ischemic heart disease
Hypertension
Diabetes
Neuro-degenerative
disease (Parkinsons,
Alzheimers)
Global deterioration
(Dementias)
           Driver 3: Acute Disease



Acute presentations
Interventions
Post elective care
Post-operative
monitoring
                     Driver 4: Diagnostics

                  History
        Special
                            Exam
         Tests


                                   Medical
Imaging
                                   Records

                  Patient

 Peak                             Blood
 Flow                            Pressure    Only a
                                             SNAPSHOT of a
          ECG               O2 Sats          patient’s health
                  Blood
                  Tests
BSN for Healthcare
                Dynamic
                Continuous use 24/7
                Preventative
                Earlier diagnosis
                Home-based
                Post-operative monitoring
                Unobtrusive
                Minimal interventions
                Improving Quality-of-Life
                Anytime
                Anywhere
                Anybody
                           The Ageing Body




Brain and nervous system
                                             Respiratory system




Visual and sensory systems




                                             Musculoskeletal system


   Circulatory system
                      Driver 4: Diagnostics

                  History
        Special
                            Exam
         Tests


                                   Medical
Imaging
                                   Records

                  Patient

 Peak                             Blood
 Flow                            Pressure    Only a
                                             SNAPSHOT of a
          ECG               O2 Sats          patient’s health
                  Blood
                  Tests
         Intelligent




                            We
     t
   en




                       ar ab
bi
    Am




                             le
                                                                 WiBro
                                                   802.16e
                                                                 CDMA 2000
                                                   (WiMAX)
                                                                 802.11 (WLAN)
                                                   HSDPA/HSUPA
                                                                 802.20 (MBWA)
                                                   LTE-UMTS


                             WiBro
        802.16e              CDMA 2000
        (WiMAX)              802.11 (WLAN)
        HSDPA/HSUPA          802.20 (MBWA)
        LTE-UMTS




                                   WSH

  WSH

                       WSH
               WSH           WSH
ASN



                                MSN
         MSN

                     MSN
                                    MSN
 MSN




                                             BSN
Sensing Development



                              Cardionetics   SAPHE environmental Blob sensor
                                 ECG

SAPHE eAR sensor




                                                         PIR sensors

                         SAPHE
SAPHE low power radio   mobile hub
      module                             Door sensors
                              How Sensor
                        e-AR: e-AR does it work?

                                      Tiny vestibular organ

                                      3 semicircular canals or hollow
                                      tubes

                                      Each tube detects the 3
                                      different motions: pitch (x), roll
       z                              (y) and yaw (z)


                                      Each tube filled with liquid,
                                      and the tube contains millions
                                      of microscopic hairs

y                   x
    Accelerometer
                           Running Gait

                                               Propulsion peak – propulsion
Impact peak-                                   of body forward (i.e. marking
the impact                                     the end of deceleration and




               Force
(shock) of                                     the beginning of
the foot to                                    acceleration)
the ground



                       0       0.1               0.2

                              Time (s)
     Initial   Stance phase          Toe off           Swing phase   Initial
     contact      reversal                               reverse     contact
e-AR Ground Reaction Force
                                                         e-AR Sensor and Ankle injury

                     Accelerometer readings of the subject were
                     recorded before and after the injury, and when the
                     subject is fully recovered


                     Distinctive patterns were found when the subject
                     was suffering from the ankle injury


                           FFT of Normal Walking                                            FFT of Walking with Leg Injury                                     FFT of Walking when Recovered
FFT




      1   51   101   151    201    251   301       351   401   451   501   1   51   101   151   201     251    301     351   401   451   501   1   51   101   151   201    251    301    351   401   451   501




                     Before Injury                                                        After Injury                                                         Fully Recovered
                 Ankle injury – Cont’d

STSOM – different clusters are
formed for the different gait
patterns (using features from FFT)


KNN – clusters are formed for
different gaits (using features from   Normal gait

wavelet transform), and the
recognition accuracy is above
90%




                                       Injured gait
                             Clinical Gait Analysis
Gait abnormalities




    Propulsive gait              Scissors gait            Spastic gait          Steppage gait              Waddling gait

Typical associated diseases

  - Carbon monoxide          - Stroke                 - Brain abscess        - Guillain-Barre syndrome   - Congenital hip
  poisoning                                                                                              dysplasia
                             - Cervical spondylosis   - Brain tumor          - Herniated lumbar disk
  - Manganese poisoning      with myelopathy                                                             - Muscular dystrophy
                                                      - Stroke               - Multiple sclerosis
  - Parkinson's disease      - Liver failure                                                             - Spinal muscle
                                                      - Head trauma          - Peroneal muscle atrophy
                                                                                                         atrophy
  - Temporary effects from   - Multiple sclerosis
                                                      - Multiple sclerosis   - Peroneal nerve trauma
  drugs
                             - Pernicious anemia
                                                                             - Poliomyelitis
                             - Spinal cord trauma
                                                                             - Polyneuropathy
                             - Cerebral palsy
                                                                             - Spinal cord trauma
Benefits to Patients
•   Truly pervasive, easy to wear and require minimal user
    interaction
•   Early detection of the onset of the disease to avoid
    complication
•   Used both for disease and well-being monitoring
•   Smart to wear, multi-function (e.g with integrated music player)
    to avoid stigmatising
•   Sensing under normal physiological conditions
•   Reconfigurability of the devices means constant improvement
    of the system capability
•   Intelligent ambient sensing can ultimately replace existing
    security and monitoring devices, and therefore brings
    significant cost benefit
Benefits to Health and Care Providers

•   Early detection means well informed care activities and
    improve resource management
•   Trend analysis and decision support simplifies care workflow
    management and decreases (improves) staff/client ratio
•   Truly pervasive, easy to install and customisation suggest
    minimal additional work for system deployment
•   Sensing under normal physiological conditions ensures
    improved patient compliance and acceptance
•   Reconfigurability of the devices means the ease of adaptation
    of the care/monitoring provision as the condition of the patient
    changes
•   Pooled population data provides evidence based care
    provision and viable financial planning
                 Supported by DTI Technology Programme
www.saphe.info

				
DOCUMENT INFO
Shared By:
Categories:
Tags:
Stats:
views:22
posted:7/31/2011
language:English
pages:33