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1.
Micromachines (Basel) ; 15(1)2023 Dec 29.
Article in English | MEDLINE | ID: mdl-38258188

ABSTRACT

A novel adhesion method of a sensor to a fingernail is described. Wearable sensors can provide health insights to humans for a wide variety of benefits, such as continuous wellness monitoring and disease monitoring throughout a patient's daily life. While there are many locations to place these wearable sensors on the body, we will focus on the fingertip, one significant way that people interact with the world. Like artificial fingernails used for aesthetics, wearable healthcare sensors can be attached to the fingernail for short or long time periods with minimal irritation and disruption to daily life. In this study the structure and methods of healthcare sensors' attachment and removal have been explored to support (1) the sensor functional requirements, (2) biological and environmentally compatible solutions and (3) ease of attachment and removal for short- and long-term user applications. Initial fingernail sensors were attached using a thin adhesive layer of commonly available cosmetic nail glue. While this approach allowed for easy application and strong adhesion to the nail, the removal could expose the fingernail and finger to a commercially available cosmetic nail removal (acetone-based chemical) for extended times measured in minutes. Therefore, a novel structure and method were developed for rapid healthcare sensor attachment and removal in seconds, which supported both the sensor functional objectives and the biologically and environmentally safe use objectives.

2.
Annu Int Conf IEEE Eng Med Biol Soc ; 2019: 1239-1242, 2019 Jul.
Article in English | MEDLINE | ID: mdl-31946116

ABSTRACT

A novel writing platform composed of a wearable sensor on the fingernail and classification algorithms is described. Findings from using this platform to translate fingertip writing into shapes, letters, and numbers on a range of surfaces are reported. The new wearable platform leverages an architecture with miniaturized electronic circuitry to precisely measure a set of forces in the longitudinal and transverse directions using multiple strain gauges. We find that the directional pressure patterns are translated from the fingertip to the fingernail. Deformation of fingernails in the longitudinal and transverse directions are detected by the fingernail sensor which sends the data wirelessly to a portable electronic system. Fingernail pressure patterns are categorized through signal processing to recognize a range of shapes, numbers, and letters, enabling fingertip writing recognition. Use of the writing platform following a short training session, shows human fingertip writing on multiple surfaces were automatically transcribed to a computer.


Subject(s)
Fingers , Signal Processing, Computer-Assisted , Writing , Algorithms , Humans , Nails
3.
Sci Rep ; 8(1): 18031, 2018 12 21.
Article in English | MEDLINE | ID: mdl-30575796

ABSTRACT

The dynamics of the human fingertip enable haptic sensing and the ability to manipulate objects in the environment. Here we describe a wearable strain sensor, associated electronics, and software to detect and interpret the kinematics of deformation in human fingernails. Differential forces exerted by fingertip pulp, rugged connections to the musculoskeletal system and physical contact with the free edge of the nail plate itself cause fingernail deformation. We quantify nail warpage on the order of microns in the longitudinal and lateral axes with a set of strain gauges attached to the nail. The wearable device transmits raw deformation data to an off-finger device for interpretation. Simple motions, gestures, finger-writing, grip strength, and activation time, as well as more complex idioms consisting of multiple grips, are identified and quantified. We demonstrate the use of this technology as a human-computer interface, clinical feature generator, and means to characterize workplace tasks.


Subject(s)
Biosensing Techniques , Fingers/physiology , Nails/physiology , Stress, Mechanical , User-Computer Interface , Wearable Electronic Devices , Behavior/physiology , Biomechanical Phenomena/physiology , Biosensing Techniques/instrumentation , Biosensing Techniques/methods , Humans , Motion , Sprains and Strains/diagnosis , Sprains and Strains/pathology , Task Performance and Analysis , Wearable Electronic Devices/standards , Weight-Bearing/physiology , Workload
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