Wakana Imano
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Wakana Imano has a total of 8 co-authors. Here are the top co-authors by number of shared publications:
- Birthe Dinesen
Department of Health Science and Technology, Aalborg University, Selma Lagerløfsvej 249, Aalborg, 9260, Denmark, 45 20771373
1 shared publication - Cecilie Topp
Laboratory of Welfare Technology-Telehealth and Telerehabilitation, Department of Health Science and Technology, Aalborg University, 9220 Aalborg Ost, Denmark
1 shared publication - Jens Refsgaard
Department of Cardiology, Viborg Hospital , 8800 Viborg, Denmark
1 shared publication - Josefine Dam Gade
Laboratory of Welfare Technology-Telehealth and Telerehabilitation, Department of Health Science and Technology, Aalborg University, 9220 Aalborg Ost, Denmark
1 shared publication - Kenichi Kameyama
Biomedical Engineering Laboratories, Teijin Pharma Ltd., Tokyo 191-8512, Japan
1 shared publication - Knud Larsen
Laboratory of Welfare Technology-Telehealth and Telerehabilitation, Department of Health Science and Technology, Aalborg University, 9220 Aalborg Ost, Denmark
1 shared publication
Latest Publications
- Open Access
Non-Contact Respiratory Measurement Using a Depth Camera for Elderly People
Measuring respiration at home for cardiac patients, a simple method that can detect the patient’s natural respiration, is needed. The purpose of this study was to develop an algorithm for estimating the tidal volume (TV) and respiratory rate (RR) from the depth value of the chest and/or abdomen, which were captured using a depth camera. The data of two different breathing patterns (normal and deep) were acquired from both the depth camera and the spirometer. The experiment was performed under two different clothing conditions (undressed and wearing a T-shirt). Thirty-nine elderly volunteers (male = 14) were enrolled in the experiment. The TV estimation algorithm for each condition was determined by regression analysis using the volume data from the spirometer as the objective variable and the depth motion data from the depth camera as the explanatory variable. The RR estimation was calculated from the peak interval. The mean absolute relative errors of the estimated TV for males were 14.0% under undressed conditions and 10.7% under T-shirt-wearing conditions; meanwhile, the relative errors for females were 14.7% and 15.5%, respectively. The estimation error for the RR was zero out of a total of 206 breaths under undressed conditions and two out of a total of 218 breaths under T-shirt-wearing conditions for males. Concerning females, the error was three out of a total of 329 breaths under undressed conditions and five out of a total of 344 breaths under T-shirt-wearing conditions. The developed algorithm for RR estimation was accurate enough, but the estimated occasionally TV had large errors, especially in deep breathing. The cause of such errors in TV estimation is presumed to be a result of the whole-body motion and inadequate setting of the measurement area.
Open AccessNon-Contact Respiratory Measurement Using a Depth Camera for Elderly People
Measuring respiration at home for cardiac patients, a simple method that can detect the patient’s natural respiration, is needed. The purpose of this study was to develop an algorithm for estimating the tidal volume (TV) and respiratory rate (RR) from the depth value of the chest and/or abdomen, which were captured using a depth camera. The data of two different breathing patterns (normal and deep) were acquired from both the depth camera and the spirometer. The experiment was performed under two different clothing conditions (undressed and wearing a T-shirt). Thirty-nine elderly volunteers (male = 14) were enrolled in the experiment. The TV estimation algorithm for each condition was determined by regression analysis using the volume data from the spirometer as the objective variable and the depth motion data from the depth camera as the explanatory variable. The RR estimation was calculated from the peak interval. The mean absolute relative errors of the estimated TV for males were 14.0% under undressed conditions and 10.7% under T-shirt-wearing conditions; meanwhile, the relative errors for females were 14.7% and 15.5%, respectively. The estimation error for the RR was zero out of a total of 206 breaths under undressed conditions and two out of a total of 218 breaths under T-shirt-wearing conditions for males. Concerning females, the error was three out of a total of 329 breaths under undressed conditions and five out of a total of 344 breaths under T-shirt-wearing conditions. The developed algorithm for RR estimation was accurate enough, but the estimated occasionally TV had large errors, especially in deep breathing. The cause of such errors in TV estimation is presumed to be a result of the whole-body motion and inadequate setting of the measurement area.