Unique ID issued by UMIN | UMIN000045853 |
---|---|
Receipt number | R000052345 |
Scientific Title | Skin condition estimation via sensing data from mobile and wearable devices |
Date of disclosure of the study information | 2021/10/25 |
Last modified on | 2021/10/25 14:20:34 |
Skin condition estimation via sensing data from mobile and wearable devices
Skin condition estimation via sensing data from mobile and wearable devices
Skin condition estimation via sensing data from mobile and wearable devices
Skin condition estimation via sensing data from mobile and wearable devices
Japan |
Acne
Dermatology | Adult |
Others
NO
In this study, we verify the possibility of estimating skin condition using sensing data obtained from smartphones and wearable devices, with the goal of preventing skin condition deterioration in advance.
Efficacy
The skin images recorded during the 60 days of the study will be judged according to the criteria of Joint Acne Image Grading and Counting via Label Distribution Learning (1) to determine with or without acne, and will be compared with lifelog data obtained from lifestyle.
(1) X. Wu et al., "Joint Acne Image Grading and Counting via Label Distribution Learning," 2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019, pp. 10641-10650, doi: 10.1109/ICCV.2019.01074.
Observational
20 | years-old | <= |
29 | years-old | >= |
Female
1) Age: healthy adult aged 20 years or older, but less than 30 years old
2)2) Gender: Japanese females
3)Females who were fully informed of the study's purpose, contents, and conditions of participation via the web site, and who gave their free written consent with sufficient understanding.
1)Who are not pregnant
2)Who are not breastfeeding
3)Who have not had acne within a year
40
1st name | Jin |
Middle name | |
Last name | Nakazawa |
Keio University
Faculty of Environment and Information Studies
252-0882
Keio University Shonan Fujisawa Campus South Room-213 Address: 5322 Endo, Fujisawa-shi, Kanagawa Ja
0466-47-0836
jin@sfc.keio.ac.jp
1st name | Yui |
Middle name | |
Last name | Kakino |
Keio University
Graduate School of Media and Governance
252-0882
Keio University Shonan Fujisawa Campus South Room-213 Address: 5322 Endo, Fujisawa-shi, Kanagawa Ja
0466-47-0836
yuui@sfc.keio.ac.jp
Keio University
Keio research institute at SFC Consortium
Other
Keio research institute at SFC Consortium
SFC Research Ethics Committee
5322 Endo, Fujisawa-shi, Kanagawa 252-0882 Japan
0466-49-3404
somu[a]sfc.keio.ac.jp
NO
2021 | Year | 10 | Month | 25 | Day |
Unpublished
Preinitiation
2021 | Year | 09 | Month | 29 | Day |
2021 | Year | 10 | Month | 01 | Day |
2021 | Year | 10 | Month | 25 | Day |
2022 | Year | 01 | Month | 16 | Day |
In this study, we verify the possibility of estimating skin condition using sensing data obtained from smartphones and wearable devices, with the goal of preventing skin condition deterioration in advance.
2021 | Year | 10 | Month | 25 | Day |
2021 | Year | 10 | Month | 25 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000052345