Personal Identification Using a Ballistocardiogram During Urination Obtained from a Toilet Seat

Nakagawa, Arata; Kim, Juhyon; Nakajima, Koji

doi:10.14326/abe.9.233

Cited by 3 publications

(2 citation statements)

References 15 publications

(15 reference statements)

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“…We selected the Mahalanobis distance (MD) as the distance function, which has been successfully applied in various biometric systems. MD is defined as follows [34]:…”

Section: Assessment Of Pa 1) Classifier Generationmentioning

confidence: 99%

Evaluation of PPG Feature Values Toward Biometric Authentication Against Presentation Attacks

et al. 2022

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“…We selected the Mahalanobis distance (MD) as the distance function, which has been successfully applied in various biometric systems. MD is defined as follows [34]:…”

Section: Assessment Of Pa 1) Classifier Generationmentioning

confidence: 99%

Evaluation of PPG Feature Values Toward Biometric Authentication Against Presentation Attacks

et al. 2022

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“…Additionally, to address the challenges in households with multiple residents, our goal is to incorporate individual authentication features based on cardiac pulsation signals. The importance of personal identification through ballistocardial signals can also extend to the field of nursing [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Ballistocardial Signal-Based Personal Identification Using Deep Learning for the Non-Invasive and Non-Restrictive Monitoring of Vital Signs

Takahashi,

Ueno

2024

Sensors

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Owing to accelerated societal aging, the prevalence of elderly individuals experiencing solitary or sudden death at home has increased. Therefore, herein, we aimed to develop a monitoring system that utilizes piezoelectric sensors for the non-invasive and non-restrictive monitoring of vital signs, including the heart rate and respiration, to detect changes in the health status of several elderly individuals. A ballistocardiogram with a piezoelectric sensor was tested using seven individuals. The frequency spectra of the biosignals acquired from the piezoelectric sensors exhibited multiple peaks corresponding to the harmonics originating from the heartbeat. We aimed for individual identification based on the shapes of these peaks as the recognition criteria. The results of individual identification using deep learning techniques revealed good identification proficiency. Altogether, the monitoring system integrated with piezoelectric sensors showed good potential as a personal identification system for identifying individuals with abnormal biological signals.

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Large Area Ballistocardiography Enabled by Printed Piezoelectric Sensor Arrays on Elastomeric Substrates

Zalar,

Burghoorn,

Fijn

et al. 2024

Adv Materials Technologies

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Ballistocardiography (BCG) studies ballistic forces on the body generated during a heartbeat. As it is an unobtrusive detection method, that requires sensors measuring small dynamic forces. Piezoelectric sensors are ideal, but improvements in sensitivity are needed. Here, a universal method is demonstrated to obtain enhanced effective transverse charge constants by utilizing thin and long sensors fabricated upon compliant substrates. This approach is validated using the uniquely printable and patternable piezoelectric polymer, poly(vinylidene fluoride‐co‐trifluoroethylene) (P(VDF‐TrFE). Discrete sensors detect displacements of less than 1 µm, dynamic forces of ∼mN, and accelerations of ≈1 mm−1 s2. Since the sensor is screen‐printable, it is upscaled to a human‐sized array (60 × 90 cm, 255 sensors). High quality spatially resolved BCG measurements of a person is demonstrated in seated and supine positions. The obtained heart rate is verified using photoplethysmography. This development opens the door to ever‐more sensitive piezoelectric sensors, crucial for applications including and beyond healthcare.

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Personal Identification Using a Ballistocardiogram During Urination Obtained from a Toilet Seat

Cited by 3 publications

References 15 publications

Evaluation of PPG Feature Values Toward Biometric Authentication Against Presentation Attacks

Evaluation of PPG Feature Values Toward Biometric Authentication Against Presentation Attacks

Ballistocardial Signal-Based Personal Identification Using Deep Learning for the Non-Invasive and Non-Restrictive Monitoring of Vital Signs

Large Area Ballistocardiography Enabled by Printed Piezoelectric Sensor Arrays on Elastomeric Substrates

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