Title | CARE COMMUNICATOR |
Brand | SPECIAL NURSING HOME FOR THE AGED HOHOEMINOSONO |
Product / Service | SPECIAL NURSING HOME HOHOEMINOSONO |
Category | B02. Clinics, Hospitals, Retail & Facilities |
Entrant | DENTSU INC. Tokyo, JAPAN |
Idea Creation | DENTSU INC. Tokyo, JAPAN |
Idea Creation 2 | DENTSU SCIENCEJAM Tokyo, JAPAN |
Production | DENTSU SCIENCEJAM Tokyo, JAPAN |
Production 2 | AIZU LABORATORY Fukushima, JAPAN |
Name | Company | Position |
---|---|---|
Masataka Hosogane | Dentsu Sciencejam inc./Dentsu inc. | Executive Creative Director |
Toshitaka Kamiya | Dentsu Sciencejam inc./Dentsu inc. | Producer |
Keiichiro Shimada | Dentsu Sciencejam inc./Dentsu inc. | Business Developer |
Yoko Kohata | Dentsu Sciencejam inc./Dentsu inc. | Planning Director |
Yuta Takeuchi | DENTSU INC. | Technical Director |
Yasue Mitsukura | Dentsu Sciencejam inc. | Researcher |
Saori Morishita | Dentsu Sciencejam inc. | Researcher |
Satoru Suzuki | Dentsu Sciencejam inc. | Researcher |
Manaka Shinozuka | Dentsu Sciencejam inc. | Researcher |
Masayuki Hisada | Aizu Laboratory inc. | Software Director |
Jinichi Tokoyo | Aizu Laboratory inc. | Software Production Manager |
Mai Sekimoto | Aizu Laboratory inc. | Programmer |
Yusuke Yoshino | Rock’n Roll Japan kk. | Film Producer |
Hiroshi Tanizaki | Rock’n Roll Japan kk. | Film Production Manager |
Naoyuki Fujise | Freelance | Film Director |
Kaoru Suzuki | Studio Interfield corporation. | Editor |
As the people in the experiment cannot respond at all, the caregivers sometimes ask themselves ‘’ Am I giving the right kind of care? “ Needless to say, all medicine/ nursing is based on communication. Therefore, understanding the patients is the most important thing. Even if the patients cannot reply, they have feelings and emotions. In order to communicate with severe bedridden patients, it is important to provide the ways to convey their condition and feelings. That’s why we developed this app to understand how the critically injured patients feel.
We focused on biological signals, especially brain waves, as the basis of our emotion grasping technology. This way, we can easily track emotions in real time. Cooperating with Prof. Mitsukura, who is an expert in processing biological signals, we collected and analyzed brain waves more than 10 thousand samples utilizing her know-how. Testing and analyzing all combinations of brainwave frequency had not been done before. From the results, we found some patterns, e.g. when people react to things that are interested in, like, get stressed about or concentrate on. Based on these findings, we developed an algorithm for 4 presumed feelings, interest, like, stress and concentration. Furthermore, we cooperated with hardware venture neurosky and updated the algorithm to operate on commercial small electroencephalograph and on iPads. These are used in some medicine/nursing facilities already, for better caring and better communication between caregivers and the patients.
The percentage of correct answers (satisfaction) of this algorithm averaged 75%. This app is already used at some hospital, nursing facilities and also at general companies. The person using the app feels positive, as they think “we are convinced that the patients understand what we are saying”, “we can give PERSONAL care, not general care.” The greatest achievement is that we testified that patients know compassion from the family/ caregivers even if they aren’t conscious. This fact has allowed us to recover the communication between patients and caregivers/ families. These algorithms are presented at academic conferences, and is based on scientific evidence.
For the sake of communication between bedridden people and caregivers, we focus on brainwave. That is because brain responds according to human intention, feelings and behavior. Actually, in order to estimate patients’ feelings based on neuroscience, it is required to prepare expensive and complex systems. However, in the scene of caregiving, it is impossible to arrange the high-quality setup. To disseminate communication between severe patients and caregivers, even non-technologist should be able to use the system which estimate patients feeling easily. Therefore, we attempted to miniaturize an electroencephalograph and develop a mobile application which understand feelings. With this app, anyone can talk to the patients more than before, and give some treatment individually according to their responses anywhere. This will also help keep motivation up for caregivers. Also, we can expand this emotion translation know-how to the marketing fields, such as in product development and qualitative research.