Statistical approaches for personal feature extraction from pressure array sensors

Journal of Information Processing

2021

Various types of helmets exist, including industrial protective helmets, motorcycle helmets, sports helmets, and military/police helmets. By identifying individuals wearing a helmet, their name, affiliation, and qualification can be presented on a display mounted on the helmet, and sensor data collected through the helmet, such as acceleration, video, and eye-tracking data, can be labeled with the user's ID. In this paper, we propose a user identification method based on head shape using a helmet equipped with 32 pressure sensors. Our method has two functions: user identification and authentication. User identification is based on the assumption that a single helmet is shared by multiple individuals. The goal of this method is to identify which of the registered people is the person wearing the helmet. User authentication determines whether the individual wearing the helmet is the individual with the ID when the ID is provided to the system. In the evaluation, we obtained sensor values for 2 seconds 20 times from nine subjects as head shape data. The accuracy was evaluated using 5-fold cross-validation, and we achieved 100% accuracy with five sensors and 92% with two sensors for user identification and an average equal error rate of 0.076 with 32 sensors for user authentication.

Section: User Authentication Methods With Pressure Sensorsmentioning

confidence: 99%

User Identification Method based on Head Shape Using Pressure Sensors Embedded in a Helmet

Fujii

Journal of Information Processing

2021

“…This method does not use specic grip actions but natural grip actions that the user just holds the device, therefore it has not been clear that users register grip actions as they like. Iso et al proposed an user authentication method for mobile devices based on grip force during using a device [6]. This method captures grip force for few tens of seconds while using a phone, then authenticates the user, taking a long time to unlock the device.…”

Section: Related Workmentioning

confidence: 98%

Mobile Phone User Authentication with Grip Gestures using Pressure Sensors

Proceedings of the 12th International Conference on Advances in Mobile Computing and Multimedia

Tobise

Terada

et al. 2014

Self Cite

Authentication methods with password, PIN, face recognition, and ngerprint identication have widely been used, however these methods have problems of diculty in onehanded operation, vulnerability to shoulder hacking, and illegal access using ngerprint with super glue or facial portrait. From viewpoint of usability and safety, strong and uncomplicated method is required. We propose a user authentication method based on grip gestures using pressure sensors mounted on the lateral and back of a mobile phone.Grip gesture is an operation of grasping a mobile phone, which is assumed to be done instead of conventional unlock procedure. Grip gesture can be performed with one hand. Moreover, it is hard to imitate grip gestures since nger movements and grip force during a grip gesture are hardly seen by the others. We experimentally investigated the feature values of grip force and evaluated our proposed method from viewpoint of error rate.

“…This system, however, does not identify individuals, therefore, it cannot be used for user authentication. Iso et al proposed a user authentication method for mobile devices based on grip force during using a device [6]. The grip force is captured during natural use without user's intended input.…”

Section: Related Workmentioning

confidence: 99%

Mobile phone user authentication with grip gestures using pressure sensors

International Journal of Pervasive Computing and Communications

Tobise

Terada

et al. 2015

Self Cite

Purpose – User authentication is generally used to protect personal information such as phone numbers, photos and account information stored in a mobile device by limiting the user to a specific person, e.g. the owner of the device. Authentication methods with password, PIN, face recognition and fingerprint identification have been widely used; however, these methods have problems of difficulty in one-handed operation, vulnerability to shoulder hacking and illegal access using fingerprint with either super glue or facial portrait. From viewpoints of usability and safety, strong and uncomplicated method is required. Design/methodology/approach – In this paper, a user authentication method is proposed based on grip gestures using pressure sensors mounted on the lateral and back sides of a mobile phone. Grip gesture is an operation of grasping a mobile phone, which is assumed to be done instead of conventional unlock procedure. Grip gesture can be performed with one hand. Moreover, it is hard to imitate grip gestures, as finger movements and grip force during a grip gesture are hardly seen by the others. Findings – The feature values of grip force are experimentally investigated and the proposed method from viewpoint of error rate is evaluated. From the result, this method achieved 0.02 of equal error rate, which is equivalent to face recognition. Originality/value – Many researches using pressure sensors to recognize grip pattern have been proposed thus far; however, the conventional works just recognize grip patterns and do not identify users, or need long pressure data to finish confident authentication. This proposed method authenticates users with a short grip gesture.