title: Brain-machine interfaces for assistive smart homes: A feasibility study with wearable near-infrared spectroscopy.
abstract: Smart houses for elderly or physically challenged people need a method to understand residents' intentions during their daily-living behaviors. To explore a new possibility, we here developed a novel brain-machine interface (BMI) system integrated with an experimental smart house, based on a prototype of a wearable near-infrared spectroscopy (NIRS) device, and verified the system in a specific task of controlling of the house's equipments with BMI. We recorded NIRS signals of three participants during typical daily-living actions (DLAs), and classified them by linear support vector machine. In our off-line analysis, four DLAs were classified at about 70% mean accuracy, significantly above the chance level of 25%, in every participant. In an online demonstration in the real smart house, one participant successfully controlled three target appliances by BMI at 81.3% accuracy. Thus we successfully demonstrated the feasibility of using NIRS-BMI in real smart houses, which will possibly enhance new assistive smart-home technologies.
authors.forename: Takeshi
authors.initials: T
authors.lastname: Ogawa
authors.forename: Jun-Ichiro
authors.initials: J
authors.lastname: Hirayama
authors.forename: Pankaj
authors.initials: P
authors.lastname: Gupta
authors.forename: Hiroki
authors.initials: H
authors.lastname: Moriya
authors.forename: Shumpei
authors.initials: S
authors.lastname: Yamaguchi
authors.forename: Akihiro
authors.initials: A
authors.lastname: Ishikawa
authors.forename: Yoshihiro
authors.initials: Y
authors.lastname: Inoue
authors.forename: Motoaki
authors.initials: M
authors.lastname: Kawanabe
authors.forename: Shin
authors.initials: S
authors.lastname: Ishii
mesh_terms: D000203:Activities of Daily Living; D062207:Brain-Computer Interfaces; D005240:Feasibility Studies; D006801:Humans; D019265:Spectroscopy, Near-Infrared; D060388:Support Vector Machine