Diet aware dining table observing dietary behaviors over tabletop surface
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Keng-hao Chang Hao-(hua) Chu Jane Yung-jen Hsu. Diet-Aware Dining Table – Observing Dietary Behaviors over Tabletop Surface. Shih-yen Liu, Cheryl Chen, Tung-yun Lin, Polly Huang National Taiwan University. A story - motivation. Video [Script]: A man wants to control weight

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Diet-Aware Dining Table – Observing Dietary Behaviors over Tabletop Surface

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Diet aware dining table observing dietary behaviors over tabletop surface

Keng-hao Chang Hao-(hua) Chu Jane Yung-jen Hsu

Diet-Aware Dining Table –Observing Dietary Behaviors over Tabletop Surface

Shih-yen Liu, Cheryl Chen, Tung-yun Lin, Polly Huang

National Taiwan University


A story motivation

A story - motivation

  • Video [Script]:

    • A man wants to control weight

    • Doctor asks him to report his dietary habits

    • Questionnaire is cumbersome, awkward

    • Then he uses our table, everything is so easy…


Pervasive healthcare we are what we eat

Pervasive Healthcare - We are what we eat

  • It’s hard

  • Shopping receipt scanner, Mankoff et al., Ubicomp 2002

    • Analyze the purchased food items of a whole family

    • It cannot track individual intake

  • Analysis of Chewing Sounds for Dietary Monitoring, Amft et al., Ubicomp 2005

    • Infer food intake by chewing sound

    • Ambiguity


But we try differently

But, we try differently

  • Smart object approach

    • Instrument everyday dining tables

    • Not blind to what happened above the surface

  • Features:

    • Natural interaction

    • Multi-users but in individual level

  • Observed Interactions?


Target interactions

Target interactions

  • Consume food from the “personal” containers

  • Where the food comes from?

  • Transferred from the share containers to personal containers


Demonstration

Demonstration


The table design what s the magic

Load Sensor

RFID Antenna

The table design – what’s the magic?

  • Two sensor surfaces

    • RFID & Weight

  • RFID – what

    • RFID-tagged containers

  • Weight - how much

    • Weight “change” of dietary behaviors

  • Cell division

    • Concurrent person-container interactions


Weight consistency principle

Weight Decrease of

Weight Decrease of

Weight Increase of

Weight Increase of

Weight consistency principle

  • Transfer tea

  • Drink tea


1 t ransfer tea

w2

w2

w1

w1- w2

1. Transfer Tea

  • Bob pours tea from the tea pot to personal cup

  • Put on tea pot.

  • RFID tag appears

  • Weight increases w1-w2

  • Pick up tea pot.

  • RFID tag disappears

  • Weight decreases w1

  • Pour tea?

  • Weight increases w2.

Pour tea by match!


2 drink tea

w1-w2

w1

w2

2. Drink Tea

  • Bob drinks tea

Drink tea by identify “Bob”

  • Put on cup.

  • Drink tea

  • RFID tag appears.

  • Weight increases w2.

  • Pick up cup.

  • RFID tag disappears.

  • Weight decreases w1.


3 complex example

3. Complex Example

  • Bob pours tea & Alan cuts cake

  • Cut cake

  • Weight decreases w2

  • Pour tea?

  • Cut cake?

  • Weight change w

  • Pour tea

  • Weight increases w1


Method summary

Method summary

  • Transfer interactions

    • Match weight

  • Eat interactions

    • Identify personal container

  • Concurrent interactions

    • Divide cells


Experiments

Experiments

  • Chinese-style dinner scenario with three users

  • No hands, utensils on the table

  • 30 min, 100 transfer events, 60 eat events

  • Behavior Recognition Accuracy: 83.33%

    • Transfer: 81.99%

    • Eat: 88.33%

  • Weight Accuracy: 82.62 %

A

B

C


Experiment discussion

Touching table

Weight Ambiguity

10 g

Eat without Transfer

10 g

Experiment Discussion

  • Causes of misses


Conclusion

Conclusion

  • Diet-aware dining table

    • A smart object and a smart surface

    • Support natural user interaction

    • fine-grained dietary tracking at individual level

  • A nice first step in such direction.

    • 80% accuracy.

  • The whole problem can be explored more deeply.


Future work

Future work

  • To improve recognition accuracy

  • To relax constraints

  • Just-in-time persuasive technology

    • To encourage balanced diet


Questions answers thank you

Questions & AnswersThank you!

Keng-hao Chang [email protected]

National Taiwan University


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