A human-machine interface (HMI)—a communication channel between a human and an external device—is one way to turn a virtual thought into realistic action. Unlike traditional HMIs as hand operation, speech input, etc., HMIs based on bioelectrical signals have advantages of "hands-free" or "aphasia," especially for patients suffering from neurological disorders. To date, the bioelectrical signals applied to HMIs include neuron signals, as well as electrocorticogram (ECG), electroencephalogram (EEG), electromyogram (EMG), electrooculogram (EOG) signals, etc. Among these techniques, EEG, EMG, and EOG are noninvasive. EEG-based HMI is the most commonly used method and has been proven useful for paralyzed patients to communicate with the external world to relatively low cost. However, the low signal-to-noise ratio (SNR) of the scalp-recorded EEG signals (in microvolts), the lack of efficient resolution in modeling, and consequently higher requirements for the classification algorithm, as well as a long period of training, limit the wide use of EEG-based HMIs.
Furthermore, a multielectrode with electrolyte gel (usually named "wet electrode") takes much time to prepare, and the gel can only keep excellent electrical conductivity for 2 hours. These drawbacks make EEG-based HMIs stable only under favorable laboratory conditions, and unstable in daily life. Nevertheless, EMG and EOG can be used as good control signals for healthy people and even "lock-in" patients who could still blink their eyes. As to these people, EMG and EOG techniques are more practical for everyday situations than EEG-based HMIs. In particular for EOG, it is a technique serving both healthy and disabled persons. EOG is based on signal collection from the corneal-retinal potential difference in the process of eye movements. The fundus is usually defined as the negative pole and the cornea as the positive pole. The potential difference is determined in principle at least on two exposed electrodes (usually Ag/AgCl electrodes as wet electrodes) pasted around the sensitive eyes, which bring discomfort and poor aesthetics. In addition, the amplitude of EOG is very weak, which is often masked by noise and difficult to detect without sophisticated and expensive electronics. EOG would be inappropriate for some applications, such as driving a car, piloting a plane, or operating a motorized wheelchair. A noninvasive and sensitive aesthetic sensor that is usable, stable, and comfortable is desired for serving the particular groups of people discussed above to solve these problems in bioelectrical-based HMI systems.
In recent years, the fast development of nanotechnology has provided possible strategies for problems in the field of bioelectric signal collection and HMIs. Among these technologies the triboelectric nanogenerator (TENG) has unique advantages of high output, low cost, light weight, applicability of structure design, prominent stability, robustness, etc. Because TENGs can generate electricity from almost all types of mechanical motions, including touching, sliding, rotation, vibration, etc., they can serve as self-powered sensors for a similarly wide range of motions, such as touch/pressure sensors, vibration sensors, biomechanical sensors, electronic skin sensors, acoustic sensors, pulse wave sensors, synthesized multifunctional sensors, and more. For the pulse wave sensor, Zhong Lin Wang at the Georgia Institute of Technology and his colleagues at the Chinese Academy of Sciences in Beijing have reported a bionic membrane sensor that noninvasively monitors the extremely weak arterial pulse from the subject's carotid artery, chest, and wrist. This inspired them to consider whether a TENG-based micromotion sensor could be used as a novel sensing device as an alternative to traditional EOG technique and could make a significant breakthrough on the mechnosensational HMI.
The team developed a noninvasive, highly sensitive transparent, flexible, skin-friendly, low-cost, durable, and reusable TENG-based sensor for translating the real-time micromotion of eye blink into control command is presented. This mechnosensational TENG could be flexibly mounted and hidden behind an eyeglass arm to form a wearable sensor. Voltage amplitude from the msTENG is significantly larger (hundred times) than that from an EOG. On the basis of this high sensitivity, the as-fabricated msTENG smart sensor glasses are used to control household appliances with a simple signal processing circuit. Furthermore, a wireless module is introduced to develop a hands-free virtual keyboard typing system. This work for the first time brings a TENG-based sensor to the field of mechnosensational HMIs, and it promises to make a significant breakthrough on mechnosensational HMIs in conditions of daily life.
"You can set a threshold for the switch," says Wang. Only when the signal is higher than the threshold, which means you really have to blink hard, can the switch be triggered.
"Compared with previous bioelectrical-based HMI technologies such as EOG, TENG-based sensors are highly sensitive, producing signals hundreds of times that of EOG. They are stable, small, light, transparent, flexible, skin-friendly, low-cost, durable, and reusable," said Professor Hu Chenguo of the Department of Applied Physics at Chongqing University and Professor Wang Zhong Lin of the School of Materials Science and Engineering at Georgia Institute of Technology.
Source and images: Science Advances
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