I would like to thank the session chair for the introduction. Also thank everyone here for coming to my talk. My talk is about the playful toothbrush for teaching tooth brushing to kindergarten children
Playful Toothbrush CHI 2008 presentation - Presentation Transcript
Playful Toothbrush: Ubicomp Technology for Teaching Tooth Brushing to Kindergarten Children CHI 2008, Florence Italy Yu-Chen Chang, Chao-Ju Huang, Hao Chu , Peggy Chi National Taiwan University Jin-Ling Lo, Nan-Yi Hsu, Hisn-Yen Wang, Ya-Lin Hsieh National Taiwan University Hospital
Child Behavior Training
Child behavior training as important but challenging parental responsibility
The most common form of parental persuasion is verbal persuasion.
“ If you don’t brush your teeth properly and thoroughly, you are not allowed to go to sleep”.
Not effective, why not?
Verbal persuasion alone lacks proper incentive to motivate children
A Case Study: Child Tooth Brushing
Target kindergarten children (5-6Y)
Learn to care for their own oral hygiene
Average 5Y children brush only 1/4 of teeth (Rugg-Gunn)
A common scenario: candies -> improper brushing -> cavities -> dental clinic
Play-based Occupational Therapy
Pediatric occupational therapy (O.T.)
Leverage the desire of children to play to induce their behavior change willingly.
Children may not like to brush teeth, but like to play.
Add playfulness (game) into the brushing activity
Effective – full of toys in pediatric O.T. clinic.
Play-Based O.T. Limitations
(1) Children treated in clinics during regular office hours (NTU Hospital)
Many child behavior problems not observable to therapists
Eating (dinner time), brushing (before bedtime), etc.
Effective treatment is difficult.
(2) Train general performance skill rather than specific functional skill
Hand dexterity skill vs. tooth brushing skill
Improvement in general performance skills may not translate into the target functional skills
HCI/UBICOMP Opportunities
Embed digital technology into a child naturalistic living environment
Sensing to observe child behavior anytime, anywhere
Game playing to influence child behavior anytime, anywhere
Occupational therapist perspective:
From treatment clinic
To the child actual living environment (functional behaviors)
HCI/UBICOMP perspective:
From sense and track behaviors
To engage children to change behaviors
Also called Persuasive technology (by Fogg, King, and others)
Playful Toothbrush Goals
(Child) Dislike brushing
Make brushing more attractive
(Child) Habitual brushing but not properly
Teach proper brushing skill
Not replace adults’ supervision
Extend their effectiveness
Used together can overcome young children’s limited physical and cognitive abilities, such that they can successfully learn proper brushing
Sensing
Camera vision to detect children’s brushing actions
Brushing actions become game inputs
Playing
An interactive game of brushing teeth
Start with a mirror image of dirty teeth.
Brushing own teeth maps to cleaning the same virtual teeth in the mirror image.
Demo video
Playful Toothbrush Brush extension Web camera for tracking brushing motions Camera #2 to record videos for later human analysis Brushing game
Play-based Occupational Therapy Model
Playful toothbrush is a treatment program / play activity (three steps).
Volition Performance Habituation Bring enough enjoyment to attract a child to participate in the target activity. Ensure a child will have a successful experience. Set appropriate level of difficulty. Apply reinforcement to reward good performance, so increase change of repeating desirable behavior. Enough times to become a habit.
Design Considerations
Enjoyment
Bring enough fun to attract children to brushing
Associate brushing with game playing and having fun
Engagement
Simple Interaction (Not all young children can learn to operate complex devices)
Use their natural brushing actions as game inputs
Automation
Help children learn tooth brushing skill and internalize as habit
In brushing case, internalizing means doing without much thinking)
Advice adults not to interrupt children and their own motor planning, necessary for internalization of brushing motor skill
Playful Toothbrush Prototype (two main components) Vision-based brushing tracker Brushing game
Vision-based Brushing Tracker
Use one camera to detect brushing
Recognize brushing of 24 different teeth surface areas (or granularity of 2 adjacent teeth surfaces)
Mouth closed during brushing
Bristle-teeth contact area not visible to an external camera
Brush extension
Each of four faces has unique LED-pattern
Used as marker to assist camera-vision recognition
Children told not to block brush
extension from the camera
How to recognize a brushing stroke on a specific teeth surface area?
Take an example (brushing the outer surface of frontal teeth)
Three features determines this brushing stroke
Bristle rotated toward the face
Brush oriented parallel to the face
Back-and-forward motion vector
(parallel to the face)
Computer Vision Technique
Use the brush extension marker to reconstruct
Bristle rotation angle (x-axis)
Brush orientation angle (z-axis)
Brush back-n-forward motion vector
Infer the brushing stroke and its target teeth area
x (θ roll ) z (θ yaw ) y brush extension
Accuracy Test (vision-based brushing tracker)
13 kindergarten children (72-81 months)
Recorded 48 minutes of their brushing videos
Compare human-read brushing strokes (ground-truth) and machine-recognized brushing strokes
Machine-recognized accuracy 90%
Need not be perfect. Occasional error in games has little effect.
Start with a virtual mirror image of the children’s own uncleaned teeth
Grouped into 24 teeth surface areas
“ 1” appears next to the first cleaning target
7 layers of plaques were drawn, requiring 7 brushing strokes
Each brushing stroke removes one layer of plaque
Combine audio feedback: Do-Re-Mi-Fa ..
No game response for brushing other teeth areas
Brushing Game
After 1st area is complete, “2” appears next to the 2 nd target area.
Applause at the game completion
Visual-audio feedbacks provide a sense of accomplishment
Enforce a brushing sequence (Stillman’s brushing method)
Upper right, upper left, the lower right, and lower left
Two benefits of sequencing
Ensure brushing all teeth
Repeat this sequence enough time -> “do without thinking”
2 3 2
User Study
Two questions guided our user study
How effective is the Playful Toothbrush in improving the brushing skills of kindergarten children?
What aspects of brushing behaviors were affected by Playful Toothbrush?
User Study Test Subjects
13 young children (72 – 81 months) from a NTUH-run kindergarten class
5 girls and 8 boys
Written informed consent from parents
Tooth brushing is required after meals or snacks
Setup
Install our system at the kindergarten’s restroom
A video camcorder to record children’s brushing sessions
User Study Procedure (11 days spanned over 3 weeks)
Pre-trial (one day)
Familiarize with the therapists and our system
Pretest (two days)
Brushed with their own toothbrushes
Established a baseline behavior
Training (five days)
Brushed with our playful toothbrush
A trained therapist helps children understand the brushing game
Posttest (two days)
Brushed with their own toothbrushes
Measured behavior improvement from pretest
One week follow up (one day)
Brushed with their own toothbrushes
Measured behavior retention after a week
User Study: Brushing Effect
Teeth cleaning effectiveness
Red plaque disclosing dye before each brushing session (dye attached the plaque)
Oral exam (counted teeth surfaces with dye before and after brushing)
Plaque index
number of teeth surfaces with plaque / total number of teeth surfaces
Cleaning effect
Reduction of Plaque Index from before to after brushing
User Study: Brushing Behavior
By analyzing/coding brushing videos, measured 3 aspects of brushing behaviors :
Length of brushing time
Number of brushing strokes on each of 24 teeth areas
Total number of brushing strokes
User Study: Cleaning Effect Results 0 .70( 0 .14) 0 .18( 0 .10) 0 .88( 0 .14) Day 11 Follow-up 0.66(0.28) 0.16(0.07) 0.85(0.10) Average 0 .70( 0 .15) 0 .15( 0 .08) 0 .86( 0 .16) Day 10 0 .67( 0 .13) 0 .16( 0 .10) 0 .83( 0 .11) Day 9 Post - test 0.66(0.17) 0.08(0.06) 0.74(0.19) Average 0 .68( 0 .17) 0 .11( 0 .10) 0 .79( 0 .18) Day 8 0 .64( 0 .26) 0 .04( 0 .05) 0 .68( 0 .28) Day 6 0 .67( 0 .15) 0 .09( 0 .10) 0 .76( 0 .14) Day 4 Training 0 .32( 0 .21) 0 .37( 0 .18) 0 .69( 0 .25) Day 3 Pre-test Cleaning effect M ean ( SD ) After brushing M ean ( SD ) Before brushing M ean ( SD )
User Study: Brushing Behavior Results 120(36) 8.31(5.07) 239.62(107.48) Day 11 Follow-up 118(30) 8.46(4.82) 248.00(87.12) Average 99(31) 9.46(5.12) 214.31( 71.91) D ay 10 137(41) 7.46(4.89) 281.69(120.66) D ay 9 Posttest Average Training 76(45) 12.39(4.75) 190.46(138.38) Average 67(46) 13.46(5.35) 168.62(157.03) Day 3 84(53) 11.31(5.25) 212.31(137.77) Day 2 Pretest Brushing time M ean (SD) (sec) Number of unbrushed teeth areas M ean (SD) Number of brushing strokes M ean (SD)
Result Summary
(Pretest) Child subject failed to clean 37% of their teeth surfaces
After 5 training days, improvements in
Teeth cleaning effectiveness
Number of brushing strokes
Length of brushing time
Coverage of brushed teeth areas
Conclusion
Demonstrate a case study of applying HCI/UBICOMP technology in play-based occupational therapy
For teaching young children proper tooth brushing, user study results were encouraging
Other similar repetitive development tasks for young children (self-feeding, potty training, cleaning room, etc.)
This technique can make training attractive and simple for adults/children.
Examples of Other Persuasive Technologies
Sense to recognize behavior
Weight sensor underneath the tray to sense eating actions
Eating actions as game input
Play to engage behavior change
Interactive games: coloring cartoon character or penguin fishing
Case Study: Playful Tray Encourage good eating habit in young children
Sense to recognize behavior
Tilt sensor to detect drinking actions
Drinking actions are game inputs
Play to engage behavior change
Game metaphor: hydrating/dehydrating body -> watering/drying a tree
Case Study: Mug-Tree Encourage healthy habit of drinking fluid regularly
Sense to recognize dress & dressing color
Camera and Computer Vision
Play to engage behavior change
Playful explore & experiment with how different clothing color look on people
CHI 2008 poster on Tuesday
Case Study: ChroMirror Persuade people to explore more colorful dressing
Thanks Q & A
Lesson #4
Mediate, not automate
Mediation: not to replace children’s efforts but make the experience of performing more enjoyable for children
Mediation works better than automation in this case.
Lesson #1
Unpredictable behaviors from young children
Make activity recognition difficult
Randomly switch from left to right hands, swing brush wildly, head movement brushing the brush …
Observe child behaviors carefully before designing and programming the system
Lesson #2
Activity grading
Children have different physical and cognitive capabilities
Some learned fast (not challenging enough); some learned slowly (frustration)
Different levels of challenges fitting to each child’s ability
“ Play-based O.T. is about the experience of performance, or the fitness between the level of challenge in an activity and a child’s physical and cognitive capabilities.”
Lesson #3
Personalization & customization
Easily personalized and customized to environmental or human factors (preferences of children, changing performance of a child, different deployment environments).
Left hand vs. right hand
Lighting condition
Child height
Preferences about game characters
Implementation Details
Toothbrush extension weight
Not too heavy for children to cause inconvenience in brushing
Prevent child from holding the brush extension
Block the brush extension from the overhead camera
Solution: a protruding cap as separator
Camera placement
Not too high such that camera cannot see the brush extension clearly.
Not too low such that children can switch the brush extension outside camera view
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