Eye blinking is closely related to human physiology and psychology.It is an effective method of communication among people and can be used in human-machine interactions.Existing blink monitoring methods include videoo...Eye blinking is closely related to human physiology and psychology.It is an effective method of communication among people and can be used in human-machine interactions.Existing blink monitoring methods include videooculography,electro-oculograms and infrared oculography.However,these methods suffer from uncomfortable use,safety risks,limited reliability in strong light or dark environments,and infringed informational security.In this paper,we propose an ultrasound-based portable approach for eye-blinking activity monitoring.Low-power pulse-echo ultrasound featuring biosafety is transmitted and received by microelectromechanical system(MEMS)ultrasonic transducers seamlessly integrated on glasses.The size,weight and power consumption of the transducers are 2.5 mm by 2.5 mm,23.3 mg and 71μW,respectively,which provides better portability than conventional methods using wearable devices.Eye-blinking activities were characterized by open and closed eye states and validated by experiments on dfferent volunteers.Finally,real-time eye-blinking monitoring was successfully demonstrated with a response time less than 1 ms.The proposed solution paves the way for ultrasound-based wearable eye-blinking monitoring and offers miniaturization,light weight,low power consumption,high informational security and biosafety.展开更多
This paper discusses how intelligent machines have replaced humans in tasks requiring,heavy,and repetitive labor,whilst being better suited to the requirements of these jobs.The increased capacity for brute force comp...This paper discusses how intelligent machines have replaced humans in tasks requiring,heavy,and repetitive labor,whilst being better suited to the requirements of these jobs.The increased capacity for brute force computation has facilitated increased collaborative innovation between man and machines.For example,the intelligent farming machines have overcome the confines of computational power,algorithms,and data,and the next generation of intelligent farming machines is expected to interact,learn,and grow autonomously.In the future,in addition to self enhancement,humans are expected to teach machines to learn and work.Scientists and engineers will collaborate with machines to accomplish invention,discovery,and creation.For“embodied intelligence”in the farming machine context,we propose(1)deep learning should be performed iteratively via real-time interactions with the external world;(2)embodied control and self-regulation can ensure coordination between behaviors of machines and their environment;(3)intelligent farming machines are characterized by the ability to interact,learn,and grow autonomously.展开更多
基金the Natural Science Foundation of China(NSFC Grant No.62001322)the Tianjin Municipal Science and Technology Project(No.20JCQNJCo11200)+1 种基金the National Key Research and Development Program(No.2020YFB2008800)the Nanchang Institute for Microtechnology of Tianjin University for funding.
文摘Eye blinking is closely related to human physiology and psychology.It is an effective method of communication among people and can be used in human-machine interactions.Existing blink monitoring methods include videooculography,electro-oculograms and infrared oculography.However,these methods suffer from uncomfortable use,safety risks,limited reliability in strong light or dark environments,and infringed informational security.In this paper,we propose an ultrasound-based portable approach for eye-blinking activity monitoring.Low-power pulse-echo ultrasound featuring biosafety is transmitted and received by microelectromechanical system(MEMS)ultrasonic transducers seamlessly integrated on glasses.The size,weight and power consumption of the transducers are 2.5 mm by 2.5 mm,23.3 mg and 71μW,respectively,which provides better portability than conventional methods using wearable devices.Eye-blinking activities were characterized by open and closed eye states and validated by experiments on dfferent volunteers.Finally,real-time eye-blinking monitoring was successfully demonstrated with a response time less than 1 ms.The proposed solution paves the way for ultrasound-based wearable eye-blinking monitoring and offers miniaturization,light weight,low power consumption,high informational security and biosafety.
文摘This paper discusses how intelligent machines have replaced humans in tasks requiring,heavy,and repetitive labor,whilst being better suited to the requirements of these jobs.The increased capacity for brute force computation has facilitated increased collaborative innovation between man and machines.For example,the intelligent farming machines have overcome the confines of computational power,algorithms,and data,and the next generation of intelligent farming machines is expected to interact,learn,and grow autonomously.In the future,in addition to self enhancement,humans are expected to teach machines to learn and work.Scientists and engineers will collaborate with machines to accomplish invention,discovery,and creation.For“embodied intelligence”in the farming machine context,we propose(1)deep learning should be performed iteratively via real-time interactions with the external world;(2)embodied control and self-regulation can ensure coordination between behaviors of machines and their environment;(3)intelligent farming machines are characterized by the ability to interact,learn,and grow autonomously.
