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Interactive Systems Technical Design. Seminar work: Sensing & Sensors Hannu Kaski Jukka-Pekka Laitinen Miika Vahtola. Introduction 1/4. Sensing Webster: “To perceive by the senses, to detect automatically especially in a response to physical stimulus”

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interactive systems technical design

Interactive Systems Technical Design

Seminar work: Sensing & Sensors

Hannu Kaski

Jukka-Pekka Laitinen

Miika Vahtola

ISTD 2003, Sensing & Sensors

introduction 1 4
Introduction 1/4

Sensing

  • Webster: “To perceive by the senses, to detect automatically especially in a response to physical stimulus”
  • Way to achieve knowledge of the world (temperature, force, acceleration…)
  • Human senses: sight, hearing, touch, smell and taste
  • Vision usually seen as the primary sense and hearing secondary
  • Exceptions to general rules like blindness or deafness
  • Touch can also be important when interacting with systems
    • Haptic systems - systems that use touch (haptic feedback) e.g. force feedback joysticks
  • Smell and taste generally ignored within computer interfaces

ISTD 2003, Sensing & Sensors

introduction 2 4
Introduction 2/4
  • Human sensing capability in active touch
    • Differences
      • Length and velocity 10%
      • Acceleration 20%
      • Force 7%
      • Mass 21%
      • Viscosity 14%
    • Resolution
      • Pressure 0,03 N/cm2
      • Transient temperature 0,05 ºC
      • Skin displacement 20 micro meters
      • Surface texture 0,1 micro meters

ISTD 2003, Sensing & Sensors

introduction 3 4
Introduction 3/4
  • Tactile user interface is one type of sensing oriented UIs (Webster defines tactile: “of or relating the sense of touch” )
    • Interface which can be controlled by touching and may give tactile output
      • Input
        • Handheld / tablet computers
        • Computer input devices
        • Information kiosks (touch screens)
      • Output
        • Vibrator alarms (cell phones, pagers)
        • Force Feedback (Entertainment applications e.g. game controllers, robotic surgery)

ISTD 2003, Sensing & Sensors

introduction 4 4
Introduction 4/4

Sensors

  • Webster: “A device that responds to a physical stimulus (as heat, light, sound, pressure, magnetism, or a particular motion) and transmits a resulting impulse (as for measurements or operating a control)”
  • Comprised of two basic parts - a sensing element and a transducer
  • Contact/contactless sensing
  • Sensors + signal processing and logic (AI) enable “sensing” in machine domain
  • Nowadays sensors have integrated microcontrollers
  • Sensor technologies are rapidly evolving
    • Drivers: miniaturization, cost, processing power, power consumption factors
    • In particular the fact that sensors are vital technology enablers for new applications

ISTD 2003, Sensing & Sensors

human vs machine characteristics related to sensing

Problem Complexity: Human vs. Machine

Object recognition

Linguistics

Extraction of Relevant Features from Sensor Arrays

Judging

HARD

Maximum Potential Benefit

MACHINE

Thresholding

Tallying

Arithmetic

Logic

EASY

HARD

EASY

HUMAN

Human vs. Machine Characteristics related to sensing

© Thad Roppel from Auburn University

ISTD 2003, Sensing & Sensors

motivation
Motivation
  • Sensors are vital technology enablers for new applications
    • When applied in a right way they will probably ease your everyday life (e.g. intelligent environments)
  • Context-aware computing
    • “Perception without the context of action is meaningless”
      • Sensors enable context-awareness (sensor fusion important)
  • Ubiquitous and pervasive computing
  • Usability of those devices that can “sense” may be better, because sensors enable a more sophisticated user interaction
    • Possibly better user experience

ISTD 2003, Sensing & Sensors

implementation
Implementation
  • Humans and computers “sense” differently
    • Machines can only emulate real sensing (i.e. human) with the help of different kind of sensors, signal processing, microcontrollers and logic
  • OBJECTIVE: To intelligently integrate multiple sensors and multiple sensor modalities (i.e. sensor fusion) to serve the needs of Human-Computer Interaction
    • More natural and intuitive interaction between humans and computer
    • “Smart interaction” usually requires a network of sensors working in concert
    • Remember to keep in mind that systems should be build for people not vice versa
      • Natural interaction as a design paradigm when possible

ISTD 2003, Sensing & Sensors

sensor selection 1 of 2
Sensor selection 1 of 2
  • According to www.sensors-ez.com there are 1022 sensor manufacturers and tens of sensor categories
  • Excellent source of sensor related information: www.sensorsmag.com
  • Capacitance sensors (based on charge sensing)
    • Cheap, simple, no calibration
    • Enables touch (position) and proximity sensing
    • Some issues that should be noticed when implementing:
      • Good quality ground reference
      • Low impedance connections
      • Keep connections short and of low inductance
      • Stop ringing by adding a series resistor
  • Photoelectric sensors (color sensing, lasers for distance sensing)
    • Reliable, versatile
    • Able to sense objects of almost any material, size and shape

ISTD 2003, Sensing & Sensors

sensor selection 2 of 2
Sensor selection 2 of 2
  • Other sensor categories
    • Acceleration & speed
    • Acoustic (e.g. ultrasonic sensors)
    • Displacement & motion
    • Force, pressure & tension
    • Light (e.g. IR)
    • Position & tilt
    • Presense & proximity
    • RF
    • Temperature & humidity
    • Torque & vibration
    • Optical imaging based sensors (e.g. cameras)

ISTD 2003, Sensing & Sensors

how to sense using sensors sense model think act loop

measure involts, amps, ohms,henrys, farads, etc.

measurand

transduce perception to electrical signal

convert fromsignal to symbol

SENSOR

ADC

e n v i r o n m e n t

ACTUATOR

compute control action

transduce signal toheat, displacement,illumination, etc

convert fromsymbol to signal

DAC

How to ’sense’ using sensors:Sense-Model/Think-Act Loop

© Mel Siegel from CMU

ISTD 2003, Sensing & Sensors

how to implement
How to implement?
  • STEPS to systematize the sensing process:
    • Decomposition of relevant context information acquired by sensors
      • Model of discrete facts and quantitative measurements
    • Build a system based on some sensor fusion system architecture (below is one example)

© Mel Siegel from CMU

ISTD 2003, Sensing & Sensors

usual requirements for an implementation
Usual requirements for an implementation
  • Small & lightweight

-> miniaturization (HDP/ASIC/MEMS)

  • Reliable
  • Information security
  • Biocompatibility
  • Low power consumption
  • Shock proof
  • Low cost

ISTD 2003, Sensing & Sensors

application

Application

Proactive Furniture Assembly

By Stavros Antifakos, Florian Michahelles and Bernt Schiele

from ETH Zurich

http://www.vision.ethz.ch/projects/

A subproject of the Smart-Its Project that is funded in part by the Commission of the European Union and the Swiss Federal Office for Education and Science

VIDEO:

http://www.vision.ethz.ch/publ/ubicomp02.mov

ISTD 2003, Sensing & Sensors

application introduction
Application Introduction
  • an experimental case study with the IKEA PAX wardrobe
  • PROBLEM: The presentation of plans by today's instructions is neither sufficient nor satisfying
  • 3 usage modes were identified: Full-walk-through, Assistance-on-demand and Rescue-from-trap
  • OBJECTIVE: To develop Proactive Instructions for Furniture Assembly

-> better usability of instructions

  • Chosen approach was to immerse instructions into the objects of interest (i.e. parts of a wardrobe)

ISTD 2003, Sensing & Sensors

ikea s assembly instructions
IKEA’s assembly instructions

ISTD 2003, Sensing & Sensors

assembly actions and possible sensor configurations to perceive the action
Assembly actions and possible sensor configurations to perceive the action

ISTD 2003, Sensing & Sensors

detection of actions
Detection of actions
  • Simple Markov chains were designed for each action
  • States and state transition probabilities were modeled by hand -> investigations to use Hidden Markov Models in order to train those probabilities automatically are currently ongoing

force sensor

screwdriver (gyroscope)

accelerometer

ISTD 2003, Sensing & Sensors

challenges
Challenges
  • Precision vs. cost (sensors aren’t free)
    • Cheapest and most unobtrusive sensor configuration enabling a high recognition precision should be the goal
  • How to inform the user (assembler) about the next steps to be taken?
    • Parts giving notice (flashing leds, beeping)
    • Guidance through a PDA/wearable computer/smart phone (should be avoided)
  • Closed world assumption narrows down the possible applications
    • we have to be able to fully model all tasks

ISTD 2003, Sensing & Sensors

other applications 1 of 4
Other applications 1 of 4
  • Applications needing
    • Proximity sensing
    • Presense detection
    • Position sensing
    • New control interfaces etc.
  • Automotive
    • Controls and lighting
    • Safety -> Electronic Stability Program, Acceleration Skid Control, Brake Assistant, Anti-lock Braking system
    • Alarms and entry access controls
  • Computers
    • Peripheral, mouse and joystick controls
    • Tactile input/output devices (force feedback, in-keyboard ‘mouse’)
  • Handheld devices (PDAs, phones etc.)

ISTD 2003, Sensing & Sensors

other applications 2 of 4
Other applications 2 of 4
  • Biomedical/Biometrics
    • Health care, personal fitness
      • Wearable, personal health systems like AMON
        • bio-sensors (pulse, blood pressure, blood oxygen saturation, body temperature, skin perspiration, ECG)
      • Robotic surgery (with PHANTOM™-like products)

ISTD 2003, Sensing & Sensors

other applications 3 of 4
Other applications 3 of 4
  • Smart environments (e.g. home, office)
      • Access controls
      • Room light switches, remote controllers (no push buttons)
      • Appliance controls (A/V & kitchen)
      • Hidden controls and alarms (in walls, furniture)
      • Object sensing (e.g. sense when somebody touches something they shouldn't)
      • Human presence sensing (e.g. automated lights and doors)
      • Hand-wave controls -> Make objects sense (e.g. automatic faucet, power-ups)
  • Wearable computing

ISTD 2003, Sensing & Sensors

other applications 4 of 4
Other applications 4 of 4
  • Disability/elderly Aids
    • electronic assistance devices
      • reduce need for pressure or pull strength
  • Safety
    • Tool auto-shutoff (dead-man switches)
    • Child detection in unsafe areas
    • Intrusion detection
  • Security
    • 'Smart Objects' - arbitrary objects

as 'smart cards' (e.g. RFID)

  • Toys
    • Dolls, SONY’s Aibo, LEGO MindStorms

ISTD 2003, Sensing & Sensors

strengths advantages 1 of 2
Strengths / Advantages 1 of 2
  • More natural interaction, unobtrusiveness and zero activation force
    • Flexible form factors
    • Better user experience and usability
  • More intuitive usage
    • Faster and easier to learn
  • Sensors can provide/acquire information not possible to perceive by human senses
    • HC interaction may work better than human-human interaction in some aspects (e.g. machines try to serve you proactively)
    • People can acquire additional information (e.g. health state)

ISTD 2003, Sensing & Sensors

strengths advantages 2 of 2
Strengths / Advantages 2 of 2
  • Eases the life of people with disabilities
  • When deployed well, will make life easier, more comfortable and safer

ISTD 2003, Sensing & Sensors

limitations weaknesses 1 of 2
Limitations / Weaknesses 1 of 2
  • Context-understanding is challenging
    • Integration of sensors is demanding because sensed information may have overlaps or even conflicts
    • Sensor fusion techniques (AI algorithms)
  • Decrease in user’s intentional control
    • Need for profiles
  • Increase in SW inferential burden
  • Fail decisions
    • Effect on user acceptance
  • Sensors don’t work in all conditions
    • Temperature, humidity, EMC and calibration issues

ISTD 2003, Sensing & Sensors

limitations weaknesses 2 of 2
Limitations / Weaknesses 2 of 2
  • Accuracy vs. Cost
    • MEMS technology enables SoC implementations that are cheaper
  • Noise and bandwidth
    • Local processing of sensor data decreases bandwidth requirements
    • Better noise filtering techniques
  • Limited power supply
    • Processing of sensor data needs power

ISTD 2003, Sensing & Sensors

selected industrial players
Selected Industrial Players
  • Microsoft Corp. – Wireless IntelliMouse Explorer
  • Quantum Research Group – QTouch™& QMatrix™
  • SensAble Technologies Inc. –PHANTOM™
  • Sony Electronics Inc. – AIBO product family
  • The LEGO Group – MindStorms™ product family
  • VTI Technologies Oy – SCA620 series z-axis accelerometer family

ISTD 2003, Sensing & Sensors

selected international research groups and projects 1 of 3
Selected International Research Groups and Projects 1 of 3
  • Carnegie Mellon University HCI Institutewww.hcii.cmu.edu

- GM/CMU Project: Driver-Vehicle Interface

- Manipulation in a Virtual Haptic Environment Based on Magnetic Levitation

- Robotic Assistants for the Elderly

  • ETH Zurichwww.ethz.ch
    • Perceptual Computing and Computer Vision Group

- Smart-Its[with Lancaster University (UK), University of Karlsruhe (GER), Interactive Institute (SWE) and VTT (FIN)]

    • Wearable Computing Laboratory

- Wearable Microsensor Network

- Advanced care and alert portable telemedical MONitor (AMON)

  • Max Planck Institute for Biological Cyberneticswww.kyb.tuebingen.mpg.de/bu

- HapSys - High-Definition Haptic Systems

- CogVis - Cognitive Vision Systems

- ECVision

ISTD 2003, Sensing & Sensors

selected international research groups and projects 2 of 3
Selected International Research Groups and Projects 2 of 3
  • MIT Media Labwww.media.mit.edu/research
    • Context-Aware ComputingChrysler 300M IT Edition, Context-Aware Tables, Disruptive Interruptions, Electronic Necklace
    • Human DesignLearning Humans, MIThril, Project Zaurus, Shortcuts
    • Nanoscale SensingHigh-Resolution Interferometric Accelerometer
    • Object-Based MediaSmart Architectural Surfaces
    • Responsive Environments

Design Principles for Efficient Smart Sensor System, Functional Integration for Embedded Intelligence, Modular Platform for High Density Wireless Sensing, Wearable Badge

    • Robotic Life

Sensate Skin, Sociable Robots

ISTD 2003, Sensing & Sensors

selected international research groups and projects 3 of 3
Selected International Research Groups and Projects 3 of 3
    • Tangible Media

Door Collision Avoidance Sensor, Tangible Bits

  • Harvard BioRobotics Laboratorywww.biorobotics.harvard.edu

- Remote Palpation Instruments for Minimally Invasive Surgery

- Vibrotactile Sensing and Display

- Force Feedback in Surgery: An Analysis of Blunt Dissection

ISTD 2003, Sensing & Sensors

selected finnish research groups and projects
Selected Finnish Research Groups and Projects
  • Tampere Unit for Computer-Human Interaction, University of Tampere
    • Multimodal Interaction Group www.cs.uta.fi/hci/mmig/projects.htm
      • Tactile User Interfaces
      • Multimodal Interface for Persons with Low Vision and/or Hearing Impairment
      • Recognition and Synthesis of Faces, Gestures, and Actions
  • Tampere University of Technology
    • Personal Electronics group www.ele.tut.fi/research/personalelectronics
      • Smart Home
      • Wearable Computing
      • Smart Clothing

ISTD 2003, Sensing & Sensors

companies and research groups in oulu
Companies and Research Groups in Oulu
  • VTT Electronics
    • Advanced Interactive Systems www.vtt.fi/ele/research/ais/
      • Interactive Intelligent Electronics (IIE) www.vtt.fi/ele/projects/iie/
  • University of Oulu/Department of Electrical and Information Engineering http://www.ee.oulu.fi
    • Machine Vision and Media Processing Unit
    • Optoelectronics and Measurement Techniques Laboratory
  • Polar Electro Oy
    • http://www.polar.fi
  • Idesco Oy
    • http://www.idesco.fi

Proximity/focus sensing Smart Phone interfaces:

  • J-P Metsävainio Design Oy http://www.jpmdesign.fi
  • MyOrigo Oy http://www.myorigo.com

ISTD 2003, Sensing & Sensors

future developments
Future Developments
  • In near term we will see “sensing” slowly become a mainstream feature in man-machine interfaces
  • Nanotechnology will offer new possibilities because then sensors are so unnoticeable
    • We won’t know if we have drunk or eaten a sensor
    • People’s acceptance?

ISTD 2003, Sensing & Sensors

thank you
Thank you!
  • Any questions?

ISTD 2003, Sensing & Sensors