Www.inertia-technology.com Current and Future Applications for Motion and Bio Sensor Networks...

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Current and Future Applications for Motion and Bio Sensor Networks

Stephan Bosch

www.inertia-technology.comwww.inertia-technology.com

IntroductionIntroduction

Inertia Technology is a spin-off from University of Twente, The Netherlands, that brings forward the idea of Wireless Sensor Networks in Motion.


OutlineOutline


Inertia Technology Wireless Sensor Networks Motion Sensing Healthcare Applications

Activity monitoring Activity stimulation

Sports Applications Miscellaneous Applications

Activity recognition Movement-based group detection Wireless Sensor and Actuator Networks


Inertia TechnologyOverview

Inertia TechnologyOverview

Using low-cost wireless sensor network technology, Inertia captures and monitors the motion of people

and moving objects, recognizes current situations and activities, provides constructive feedback and takes appropriate actions.

Applications in Healthcare, Sports, Industry, Logistics, etc.


Inertia TechnologyFeatures

Inertia TechnologyFeatures

Smaller. Highly miniaturized platforms (sensor nodes) with low-power

microcontrollers, wireless communication and sensors. Size matters because the sensor nodes have to be easily worn by

people, embedded into objects or deployed within the infrastructure.

Smarter. Sensor nodes process data locally Sensor nodes collaborate in a network to achieve more accurate and

reliable results Accuracy increases with having multiple points of observation and

multiple types of sensors.

Wireless. No wires means reduced installation and maintenance costs. The system is autonomous, self-organizing, self-repairing and does not

require any external infrastructure.


Wireless Sensor NetworksIntroduction

Wireless Sensor NetworksIntroduction

Tiny, cheap, battery-powered nodes with:

Sensors CPU and memory Wireless transceiver


Wireless Sensor Networks Networking

Wireless Sensor Networks Networking

Ad-hoc networks of sensor nodes Self-organizing Unattended Collect data and communicate

over multiple hops Context-aware React locally to events


Environmental Monitoring

(traditional)

Oil & Gas Industry Transport and Logistics

Guidance in Emergency situations

Wireless Sensor NetworksApplications

Wireless Sensor NetworksApplications

Applications:


Wireless Sensor NetworksChallenges

Wireless Sensor NetworksChallenges

Energy efficiency Very limited resources Massive deployment - large WSN infrastructures Heterogeneity - specialized nodes (log

environmental data, check hazardous substances, fire detection, localization, etc.)

Reconfigurability - parameter tuning / complete reprogramming

Reliability - key factor in the given application domains

Programmability - user programming interface


Wireless Sensor NetworksSensor Intelligence

Wireless Sensor NetworksSensor Intelligence

Sensor nodes can sense, think, talk and act. Sensing and communication are widely

discussed. Distributed, collaborative reasoning and

actuation only recently gained attention Many AI techniques that match the specifics of

WSNs – unreliable, imprecise information, scarce resources, local processing combined with distributed reasoning.


Wireless Sensor Networks The temperature and humidity

problem

Wireless Sensor Networks The temperature and humidity

problem

So many names for similar ideas: WSN-WSAN, Smart Objects, Pervasive Systems, Ubiquitous Computing, Internet of Things...

In the end, it's all about embedding some intelligence and wireless capability into devices.

Monitoring temperature and humidity became the "standard example" in WSNs.

Although temperature and humidity are very useful, after a while you start wondering, can sensor nodes do anything more intelligent than that?


Motion SensingMotion Sensing

Motion sensors used to be large and power-inefficient

Recent advances in Micro-electro-mechanical systems (MEMS) made miniature motion sensors available

Such sensors are silicon devices with tiny moveable sensor parts on a nano scale

Power-consumption can be as low as 60 μW when measuring and 0.2 μW in standby mode

Courtesy of Sandia National Laboratories, SUMMiTTM Technologies, http://mems.sandia.gov


Motion SensingModalities

Motion SensingModalities

Available sensors: Accelerometer: measures lateral acceleration Gyroscope: measures angular velocity Compass: measures orientation relative to

Earth’s magnetic field

These sensors can respectively measure acceleration, angular velocity and orientation in a three-dimensional manner.


Motion SensingPossibilities

Motion SensingPossibilities

Movement sensors can capture a lot of information. Their potential usage is still to be explored by the community.

Latest mobile devices like mobile phones are equipped with motion sensors, creating the foundations for fun and very useful applications.


Motion Sensingin a Wireless Sensor Network

Motion Sensingin a Wireless Sensor Network

Wireless sensor nodes are equipped with motion sensors

Motion data processing: Motion data is processed locally on the sensor nodes Motion data from multiple nodes is combined to a achieve a

common goal, e.g. activity monitoring and recognition Focuses on getting reliable results out of unreliable and

imprecise sensor data. Network provides just-in-time constructive feedback to

the user Ease of installation and instant wireless connectivity

without requiring external infrastructure Low-cost and low-power operation


Motion SensingHardware

Motion SensingHardware

Wireless Sensor Nodes ProMove board

Three-dimensional accelerometer Three-dimensional compass Two-dimensional gyroscope MSP430 low-power microcontroller

48 kB flash ROM and 10 kB RAM

CC2430 802.15.4 radio + CPU (System on a Chip)


Elderly and people with chronic conditions.

Paradigm shift from care center to home-centric, person-centric healthcare & wellbeing services.

Healthcare ApplicationsHealthcare Applications

Goals: Help to improve the physical condition. Augment training and exercising. Enhance interaction with smart objects and artifacts. Build virtual “healthy” groups and improve social interaction.


Healthcare ApplicationsActivity Monitoring

Healthcare ApplicationsActivity Monitoring

Health condition and quality of life are directly influenced by the amount and intensity of daily physical activity.

This is particularly relevant to persons with chronic conditions, such as Chronic Obstructive Pulmonary Disease (COPD), asthma and diabetes. Persons suffering from these ailments enter a vicious circle, in

which being active causes discomfort, making them progressively less active and less healthy.

Monitoring the daily activity can stimulate people to perform exercises and to be more active.


Activity MonitoringApplications

Activity MonitoringApplications

Mainly: improving health and quality of life for patients with chronic diseases (e.g. COPD).

But also: healthy users that want to assess and improve their overall fitness.

Activity monitoring systems can remind, stimulate and motivate people to be more active.

Within groups with a competitive nature this could work even better.


Activity MonitoringThe Problem

Activity MonitoringThe Problem

We need to obtain a reliable measure of the user’s level of activity.

The solution needs to be unobtrusive: User needs to wear it during his daily life. Directly measuring the user’s energy expenditure

requires measuring the user’s rate of metabolism, which is an intrusive process and therefore not a solution.

The system needs to provide feedback in an intuitive manner, without the use of a PC.


Activity MonitoringThe Basic Solution

Activity MonitoringThe Basic Solution

Provide an estimate of energy expenditure in stead of a measurement.

The estimate is obtained by measuring the amount of movement on a particular point of the subject’s body during daily life (the so-called IMA value).

A proven method is to use an accelerometer. This is limited to a single acceleration sensor

mounted near the subject’s center of mass.


Activity MonitoringRemaining Issues

Activity MonitoringRemaining Issues

Using a single accelerometer not optimal in some situations: Certain activities contribute much more to the activity

estimate than others, although energy expenditure is expected to be similar.

The set of activities considered in existing work is usually limited to only simple daily activities like walking, sitting, running etc.

How to provide feedback to the user? Simplicity is key!


Activity MonitoringEstimation Improvements

Activity MonitoringEstimation Improvements

Use more than a single movement sensor to obtain a more accurate activity level estimate.

However, there is a trade-off between the number of sensors used, their size and the obtrusiveness of the system.

Therefore, we will use small wireless sensor nodes distributed over the body of the user at key locations.


Activity MonitoringFeedback

Activity MonitoringFeedback

Use a colored light to indicate the user’s activity level.

Mount it somewhere at a fixed location in the environment.

Such a feedback device can be used intuitively. The user does not need to carry the interface. Multiple users can use the same light interface


Activity MonitoringUser Interface

Activity MonitoringUser Interface

Ambient Orb: LED-based RGB color lamp with

Displays the activity level as a color between red and green: With green meaning active

and red meaning lazy.

Supports multiple users by displaying colored ID for newly encountered users

Users interact by tapping their sensor: Two times to let orb display daily activity Three times to let orb display hourly activity


Activity MonitoringExperiments (1)


Subjects wear a node at their pant belt

Nodes record activity values in flash memory on an hourly basis.

Subjects manually record their activities in a simple diary.

At a fixed time during the day, data is extracted wirelessly from the flash records during a short meeting.




Tested multiple subjects performing various activities of interest in the course of multiple experiments.

Experiments include: home and office activities,

Three days with 9 subjects a skiing vacation,

One week and two subjects and various sports.

Tested in separate experiments of at least an hour with two to four subjects


Activity MonitoringExample Result

Activity MonitoringExample Result

Two persons with similar daily activities:


Activity MonitoringExperiment ResultsActivity MonitoringExperiment Results


Healthcare ApplicationsActivity Stimulation

Healthcare ApplicationsActivity Stimulation

Stimulate user activity without actually monitoring

Users are usually not inclined to be more active without something in return

Make being active a fun and appealing thing to do E.g. by letting the user play a game that

stimulates activity


Activity StimulationGaming

Activity StimulationGaming


Activity StimulationExample

Activity StimulationExample

Submarine game User controls small submarine on screen with

a dumbbell as controller The submarine follows the up/down

movements of the player.


Sports ApplicationsSports Applications

For professional athletes a means to quantify their level of training as well as their performance is important.

Real-time feedback is essential for quickly assessing the training efficiency, as well as preventing overuse injuries.

The Inertia system applies both to individual athletes that seek to improve their performance and teams where coordination is a key factor.

Current Applications Professional Cycling

Assessing proper bicycle fit by measuring joint angles and cyclist posture

Future sports of interest Skating (posture) Running


Sports ApplicationsCycling: Bicycle Fit

Sports ApplicationsCycling: Bicycle Fit

Proper bicycle fit is essential for comfort, safety, injury prevention and peak performance [1]

Saddle height Adjusted such that the knee

should be flexed 25° to 30° from full extension

Stem and handlebar height Hands on brakes - torso should

flex to 45° Hands in the drops – torso should

flex to 60°[1] Silberman MR, Webner D, Collina S, Shiple BJ. Road bicycle fit.Clin J Sport Med. 15(4):271-6, Jul. 2005


Sport ApplicationsBicycle Fit: FatigueSport Applications

Bicycle Fit: Fatigue

Due to fatigue during cycling, kinematics vary among joint angles (torso, knee, ankle) [2]

Injuries are the result from biomechanical alterations associated with fatigue.

Fatigue related injuries: primarily repetitive strain injuries (RSI) Overuse knee pain (42% - 62% of recreational

cyclists)[2] Dingwell, J.B.; Joubert, J.E.; Diefenthaeler, F.; Trinity, J.D., Changes in Muscle Activity and Kinematics of Highly Trained Cyclists During Fatigue, IEEE Transactions on Biomedical Engineering, vol.55, no.11, pp.2666-2674, Nov. 2008


Sports ApplicationsBicycle Fit: Existing Solution

Sports ApplicationsBicycle Fit: Existing Solution

Camera system Vicon, Optotrak,… Active/passive

markers Measures distances Very accurate (0.1°,

1 mm) Works only indoors Works only in a

limited space


Sports ApplicationsBicycle Fit: Wireless Sensor

Alternative

Sports ApplicationsBicycle Fit: Wireless Sensor

Alternative

(Wireless) inertial sensing system Portable, unobtrusive A lot of information: acceleration, angular

velocity, orientation How about accuracy?


Sports ApplicationsBycicle Fit: Experiments (1)



Sports ApplicationsBicycle Fit: MethodSports ApplicationsBicycle Fit: Method

What we need to measure: Thigh-shank (TS) peak

angles Shank-foot (SF) peak angles

Data processing activities: Establishing orientation of

each node (difficult) Computation of TS and SF

angles Peak detection Computation of accuracy


Sports ApplicationsBicycle Fit: Sensor Orientation

Sports ApplicationsBicycle Fit: Sensor Orientation


Sports ApplicationsBicycle Fit: Result Comparison

Sports ApplicationsBicycle Fit: Result Comparison


Sports ApplicationsBicycle Fit: AccuracySports Applications

Bicycle Fit: Accuracy

Average TS error: 2.06 Average TS STD: 0.85 Average SF error: 4.65 Average SF STD: 2.27


Industrial ApplicationsManufacturing

Industrial ApplicationsManufacturing

Assembly and testing processes in industrial manufacturing production lines.

Distributed system composed of wireless sensor nodes worn by the workers, embedded into the tools and deployed within the infrastructure.

Sensors self-organize and recognize online the currently performed activity – assistance, verification, training.


Industrial ApplicationsDWARF

Industrial ApplicationsDWARF


Movement-based Group Detection Overview

Movement-based Group Detection Overview

Communication of movement data

Synchronization of movement data

Computation of the correlation coefficient

Group objects and persons based on correlated movement Which sensors are moving

together?

-100

-50

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

X

Y Corr = 0.896


Movement-based Group DetectionLogistics and Transport Applications

Movement-based Group DetectionLogistics and Transport Applications

Incorrect loading and delivery – can be checked by inertial sensors.

Detect groups of goods or vehicles based on their movement


Movement-based Group DetectionOn-body Applications

Movement-based Group DetectionOn-body Applications

Automatic association of nodes moving together: Worn on the body Objects the persons is

interacting with Possible functionality:

Context and activity recognition

Multimodal HMI Build trusted networks Extendable to groups of

people that need to coordinate movements.


http://www.youtube.com/watch?v=ZzWYO5dbo1M

Wireless Sensor and Actuator NetworksExample

Wireless Sensor and Actuator NetworksExample

Movement coordination of autonomous vehicles.

Inertial sensing + Wireless communication + Control loop = Swarm of moving vehicles.

Everything running on sensor nodes!

Demo video:


Thank you!

Www.inertia-technology.com Current and Future Applications for Motion and Bio Sensor Networks...

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