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Abstract Innovative human–machine interfaces (HMIs) have attracted increasing attention in the field of system control and assistive devices for disabled people. Conventional HMIs that are designed based on the interaction of physical movements or language communication are not effective or appliable to severely disabled users. Here, a breath‐driven triboelectric sensor is reported consisting of a soft fixator and two circular‐shaped triboelectric nanogenerators (TENGs) for self‐powered respiratory monitoring and smart system control. The sensor device is capable of effectively detecting the breath variation and generates responsive electrical signals based on different breath patterns without affecting the normal respiration. A breathing‐driven HMI system is demonstrated for severely disabled people to control electrical household appliances and shows an intelligent respiration monitoring system for emergence alarm. The new system provides the advantages of high sensitivity, good stability, low cost, and ease of use. This work will not only expand the development of the TENGs in self‐powered sensors, but also opens a new avenue to develop assistive devices for disabled people through innovation of advanced HMIs.
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Inclusion in human–machine interactions
Human–machine interactions (HMIs) describe how humans engage various systems, including those that are smart, autonomous, or both. Most HMIs either allow the human to control the machine (an instrument panel), allow the machine to obtain data (a heart monitor), or even both (a virtual reality setup). HMIs may be placed in three broad classes. In one class, the individual is active in the interaction—that is, the individual is the user or purchaser of a technology such as an automobile. In another class, the user is passive but consenting in the interaction—that is, the interaction occurs with their consent, such as the use of devices for medical diagnosis. There is also a class in which the user is passive and nonconsenting in the interaction, such as the use of facial recognition for law enforcement purposes.
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- Award ID(s):
- 1836952
- PAR ID:
- 10344295
- Date Published:
- Journal Name:
- Science
- Volume:
- 375
- Issue:
- 6577
- ISSN:
- 0036-8075
- Page Range / eLocation ID:
- 149 to 150
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1126/science.abf2618
