TY - GEN
T1 - VibroScale
T2 - 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and 2020 ACM International Symposium on Wearable Computers, UbiComp/ISWC 2020
AU - Zhang, Shibo
AU - Xu, Qiuyang
AU - Sen, Sougata
AU - Alshurafa, Nabil
N1 - Publisher Copyright:
© 2020 Owner/Author.
PY - 2020/9/10
Y1 - 2020/9/10
N2 - Smartphones, with their ubiquity and plethora of embedded sensors enable on-the-go measurement. Here, we describe one novel measurement potential, weight measurement, by turning an everyday smartphone into a weighing scale. We describe VibroScale, our vibration-based approach to measuring the weight of objects that are small in size. Being able to objectively measure the weight of objects in free-living settings, without the burden of carrying a scale, has several possible uses, particularly in weighing small food items. We designed a smartphone app and regression algorithm, which we termed VibroScale, that estimates the relative induced intensity of an object placed on the smartphone. We tested our proposed method using more than 50 fruits and other everyday objects of different sizes and weights. Our smartphone-based method can measure the weight of fruit without relying on an actual scale. Overall, we observed that VibroScale can measure one type of object with a mean absolute error of 12.4 grams and a mean absolute percentage error of 7.7%. We believe that in future this approach can be generalized to estimate calories and measure the weight of various types of objects.
AB - Smartphones, with their ubiquity and plethora of embedded sensors enable on-the-go measurement. Here, we describe one novel measurement potential, weight measurement, by turning an everyday smartphone into a weighing scale. We describe VibroScale, our vibration-based approach to measuring the weight of objects that are small in size. Being able to objectively measure the weight of objects in free-living settings, without the burden of carrying a scale, has several possible uses, particularly in weighing small food items. We designed a smartphone app and regression algorithm, which we termed VibroScale, that estimates the relative induced intensity of an object placed on the smartphone. We tested our proposed method using more than 50 fruits and other everyday objects of different sizes and weights. Our smartphone-based method can measure the weight of fruit without relying on an actual scale. Overall, we observed that VibroScale can measure one type of object with a mean absolute error of 12.4 grams and a mean absolute percentage error of 7.7%. We believe that in future this approach can be generalized to estimate calories and measure the weight of various types of objects.
KW - accelerometer
KW - automatic measurement
KW - food weight estimation
KW - fruit calorie estimation
KW - mobile application
KW - smartphone
KW - ubiquitous computing
KW - vibration
KW - weighing scale
UR - https://www.scopus.com/pages/publications/85091839376
UR - https://www.scopus.com/inward/citedby.url?scp=85091839376&partnerID=8YFLogxK
U2 - 10.1145/3410530.3414397
DO - 10.1145/3410530.3414397
M3 - Conference contribution
AN - SCOPUS:85091839376
T3 - UbiComp/ISWC 2020 Adjunct - Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers
SP - 176
EP - 179
BT - UbiComp/ISWC 2020 Adjunct - Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers
PB - Association for Computing Machinery
Y2 - 12 September 2020 through 17 September 2020
ER -