Soft human–machine interfaces: design, sensing and stimulation
Human–machine interfaces (HMIs) are widely studied to understand the human biomechanics and/or physiology and the interaction between humans and machines/robots. The conventional rigid or invasive HMIs that record/send information from/to human bodies have significant disadvantages in practice for long-term, portable, and comfortable usages. To better adapt to natural soft skins, soft HMIs have been designed to deform into arbitrary shapes, and their bendable, stretchable, compressible and twistable properties offer a huge potential in future personalized applications. This paper presents a survey on various soft HMIs in terms of design, sensing, stimulation as well as their applications. Specifically, tactile/motion/bio-potential sensors are categorized for recording various data from human bodies, while stimulators are discussed for information feedback and motion activation to human bodies. It is anticipated that soft HMIs will promote the interaction among humans, machines/robots and environment to achieve desired coexisting-cooperative-cognitive function in a robot system, named as Tri-Co Robot, for the human-centered applications, such as rehabilitation, medical monitoring and human–robot cooperation.
KeywordsHuman–machine interfaces Flexible/stretchable electronics Tactile sensors Biological healthy monitoring Stimulation feedback
Human–machine interfaces (HMIs) refer to the studies of the two-way transmission of information between humans and machines (such as computers or robots) (Liu et al. 2017). Recording and interpreting physical and/or physiological information of humans is a key point to allow the robots interacting with humans. Conventional rigid HMIs have been widely applied in robotic systems, such as rehabilitation robots (Yu et al. 2015; Yi et al. 2017), motion gesture monitoring (Uchida et al. 2004), and biological health monitoring (Brown et al. 2014). However, they generally lead to the uncomfortablity of the human body and unstable signal in motion (He et al. 2015; Kim et al. 2013; Ju and Liu 2017) by directly laminating onto the skin surface (Wang et al. 2015; Hammock et al. 2013). Alternatively, soft HMIs based on flexible/stretchable electronics can fulfil the requirements of the next-generation HMIs that offer the sensing functions of conventional, rigid technologies but also with the ability to be stretched, compressed, twisted, bent, and deformed into arbitrary shapes (Rogers et al. 2010; Huang et al. 2017). They overcome the fundamental mis-match in mechanical and material properties with human bodies, and thus would realize innovative applications that are impossible for rigid HMIs. It is very important to design the soft HMIs to adapt to the musculoskeletal deformations including local deformation of skin/muscule and global motion of human (Lipomi et al. 2011; Kim et al. 2011). It is beneficial to achieve the expected coexisting-cooperative-cognitive robot (Tri-Co Robot) system for the purpose of rehabilitation, medical monitoring and human–robot cooperation (Ding et al. 2017).
The soft tactile sensors are designed as superskins with higher sensitivity and time–space resolution to monitor pressure, strain, and sound information for HMI applications. Soft pressure sensors based on capacitive sensing arrays (Lipomi et al. 2011; Mannsfeld et al. 2010; Tee et al. 2012), piezoelectric materials (Uchida et al. 2004), porous pressure sensitive rubber (Lim et al. 2015), and ionic gels (Sun et al. 2015) are designed to monitor biological signals, which have been widely applied to pressure visualization and reproducing the tactile sensing abilities. Stretchable strain sensors based on piezoresistive materials (Ying et al. 2012), ZnO nanowires (Xiao et al. 2011), metal coils (Kim et al. 2012; Huang et al. 2014), and liquid metals (Jeong et al. 2016) are developed to detect human gestures. Artificial electronic eyes have been extensively applied to robot navigation to assist people for complicated tasks (Ji et al. 2008; Ji and Liu 2009; Guo et al. 2017). Sound signals acquired by piezoelectric materials (Abdeljaber et al. 2015; Rajabi et al. 2015) and EMG electrodes (Shriver et al. 2001) have also been widely adopted in speech analysis and recognition, which show novel interaction ways for playing computer games.
Motion sensing, including measuring joint angles, linear displacements, velocities and accelerations of humans and robots, is critical for the human–machine interaction to accomplish complicated and dynamic tasks (Wang et al. 2012). For example, the artificial limbs integrated with motion sensors can be precisely manipulated and controlled in a closed-loop manner (Watanabe et al. 2006). A large number of soft motion sensors have been designed for HMI applications. Soft joint angle sensors based on graphene, smart gloves, and liquid metal are designed to monitor human gesture and control the robot to reproduce the action (Flynn et al. 2014). Stretchable strain sensors based on carbon-black (Lu et al. 2012), liquid metal (Huang et al. 2014), and ionic gel (Sun et al. 2015) are developed for skin strain, human motion and gestures detection. Velocity and acceleration sensors are widely applied to measure human gestures and positions, and the corresponding algorithms are proposed for classifications for controlling the external machines via human motion state (Park et al. 2016).
Electrophysiology signals from human bodies have also been used in HMI applications, and replaced the conventional electrodes for recordings of electromyography (EMG), electroencephalogram (EEG), and electrooculography (EOG) of biological health (Domazet 2016; Han et al. 2016; Saproo et al. 2016; Löhrer et al. 2015; Mavadati 2015). In the state-of-the-art, the flexible/stretchable bio-potential electrodes are designed and developed to provide long-term and stable biological signal recordings (Rogers 2013; George et al. 2014; Hu and Wang 2015). The feature extraction and pattern recognition algorithms are proposed to classify the biological signals, and the corresponding control signals are generated through the patterns for controlling the external actuators (Gao et al. 2016; Huang et al. 2016; Lee et al. 2016).
Additionally, stimulations from electronic devices to humans is another kind of important interaction modes that make humans sense external environment or establish closed-loop control between humans and machines/robots via the soft HMIs integrated with stimulators and actuators (Xu et al. 2016; He et al. 2017). Electrical stimulation evokes tactile sensations within the skin at the location of a small, cutaneous electrode by passing a local electric current through the skin to stimulate cutaneous afferent fibers (Haviv et al. 2017; Martin et al. 2017). Feedback to humans via different stimulators can be divided into electrotactile stimulation, sound and light stimulation, braille display, and EEG-EMG stimulation. Electrotactile stimulation is realized with the external voltage supplied from electronic devices (Ying et al. 2012). Sound and light stimulation are designed for biological feedback to improve humans’ speech abilities (Calomeni et al. 2013). Braille display based on electroactive polymer actuators (EAP) is designed and developed for visually impaired people to touch and know the outside world more vividly (Marette et al. 2017; Martinez et al. 2012; Bishop-Moser and Kota 2017). EEG-EMG stimulation is proposed for human rehabilitation with the help of robots. Additionally, there are also researches on rendering sense of taste and smell with electronic devices, such as a taste stimulators and artificial noses (Ranasinghe and Do 2016; Löffler et al. 2015; Zou et al. 2015).
From 2000 to 2010 Flexible Microprocessors and microsensors were widely designed to flexible HMIs which accelerated the development of electronic skin (E-skin) significantly ranging from robotics to healthcare. Someya et al. developed flexible organic field-effect transistors (OFETs) for large-area integrated pressure-sensitive sheets with active matrix readout (Somarajan et al. 2013; Someya et al. 2004), and the stretchable active-matrix organic light emitted diodes (AMOLED) for large-area integrated pressure-sensitive sheets pressure visualization with pressure-sensitive rubber (Sekitani et al. 2009a, b). A cybernetic hand was integrated with infrared radiation sensors to control hand motions. Rogers et al. designed flexible artificial electronic eyes which provided an effective way for robots to connect and communicate with people (Ko et al. 2008). Bao et al. investigated highly sensitive capacitive pressure sensors with microstructural elastomeric dielectrics for large sensitive mechanical force sensing (Mannsfeld et al. 2010). The flexible optoelectronics including light-emitting diodes (LEDs) and organic photovoltaics (OPVs) were integrated with human skin to show the skin pressure distribution (Wu and Wang 2016).
From 2010 to the present Stretchable HMI has been attracted more and more attentions. The motion features were detected by the soft electronics integrated with multi-strain sensors to control the external actuator (Ying et al. 2012). Javey et al. designed an interactive HMI system integrated with pressure sensitive skin, organic transistor array and LEDs (Takei et al. 2010), and the pressure distribution was provided to interact with external surroundings (Qian et al. 2016). A wearable interactive HMI based on pressure and strain sensors was applied to personal mobile electronics and the Internet of Things (Fan et al. 2014). Stretchable EMG electrodes were designed with serpentine structure to recognize different human gestures, and different control commands were generated to the external actuators (Jeong et al. 2013). The artificial skin integrated with the EMG sensor, strain sensor, and pressure sensor, used as prosthetic skin, was designed to operate complicated tasks, such as grasping the cup, and tapping on the keyboard (Kim et al. 2014). The acoustic sensor laminated onto the human throat collected the features signal with different speech and generated control commands to control the computer game (Liu et al. 2016). Transparent ZnO sensors were designed and fabricated to recognize the gestures of different fingers without power supply (Pradel et al. 2014). A self-powered HMI with cut-paper-based self-charging power unit was used to practical and medical applications by Wang et al. (Huang et al. 2017; Kim et al. 2014; Pang et al. 2017). Transparent HMI with porous pressure sensitive rubber sensors and strain gauges were designed to control a robot arm remotely (Lim et al. 2015), and the epidermal electronic system with the EMG sensor, strain sensor, humidity sensor, and temperature sensors was also used as an HMI to control the robot arm (Xu et al. 2016).
There were several review articles about the flexible/stretchable electronics which have been applied to soft robot, biological healthy monitoring, electronic skin (E-skin), and detection of human hand motion (Yi et al. 2017; Kim and Rogers 2008; Argall and Billard 2010; Gu et al. 2017; Lee et al. 2017; Zhao et al. 2017; Polygerinos et al. 2017; Xue et al. 2018). Lu discussed flexible and stretchable electronics for soft robot (Lu and Kim 2014). Bao et al. introduced the brief history and development of E-skin, and coexistent problems about its designs and applications (Hammock et al. 2013). Wang et al. reviewed the recent process of E-skin with multi-mode force sensing, temperature, and humidity detection, as well as self-healing abilities (Wang et al. 2015). However, most of these surveys mainly focused on the designs and developments of the stretchable devices in different applications, soft HMIs are not systemically reviewed for the design and applications for human–machine interaction. The stretchable electronics technology enables the next generation of electrodes for soft HMIs (Kim et al. 2014). This paper reviews the development of soft HMIs based on stretchable electronics, including design methods, sensing/stimulation principles, and interaction applications. Material and structural design for stretchability are introduced in Sect. 2. Three typical HMI modes and their applications are reviewed in Sect. 3. Stimulation from electronic devices to humans is introduced in Sect. 4. The whole paper is concluded with remarks in Sect. 5.
2 Structural design of flexible/stretchable components
Material selection and structural design are important to improve the stretchability of HMIs. Recent progresses on the developments of stretchable materials have enabled a number of intrinsically stretchable devices (Sundar et al. 2004; Cheng et al. 2016; Yu et al. 2016; Ding et al. 2017), such as liquid metal, hydrogels and rubber. Epidermal strain sensor based on liquid metal and PEIE-polydimethylsiloxane (S3-PDMS) elastomer substrate could be stretched to 50% and shows excellent compatibility with human skin (Jeong et al. 2016; Chen et al. 2014). PDMS microfluidic devices were also adopted in biomedical applications (Huang et al. 2014; Liu et al. 2015), where PDMS was widely used in the soft devices, due to the advantages of softness, stretchability, transparency, easy fabrication, bio-compatibility, chemical inertness, stability, and adhesive (Yabuta et al. 2003). Organic polymer with mechanical and electrical self-healing properties was applied to electronic skin in soft robotics and biomimetic prostheses (Tee et al. 2012).
- (1)Several approaches have been utilized to fabricate stretchable interconnect structures (Fig. 3a): patterned thin film on the prestrained substrate to generate nonplanar buckled structures (left frame) (Huang et al. 2010; Su et al. 2017), serpentine film on stretchable substrate, such as wrinkled, serpentine structures (center frame) (Gonzalez et al. 2008; Zhang et al. 2013, b), and self-similar serpentine structure (right frame) (Huang et al. 2017; Zhang et al. 2013; Li et al. 2013; Su et al. 2015; Dong et al. 2017; Huang et al. 2015). The serpentine interconnects were usually designed for large stretchability (Su et al. 2012). However, the freestanding format was a challenge for encapsulation. Soft microfluidic assembly technique is studied to address this challenge (Xu et al. 2014). The self-similar serpentine structure was enhanced version of serpentine design for hyper-stretchable devices, simutaneously with high areal coverage shown in Fig. 3f (Huang et al. 2017; Zhang et al. 2013; Li et al. 2013; Su et al. 2015; Dong et al. 2017; Huang et al. 2015; Son and Kim 2013). Structural optimized strategies were proposed to improve the stretchability of the rectangle electrode (Jeong et al. 2013; Xu et al. 2015). Topology optimization strategies were proposed to optimize the stretchability of electronic devices the with soft mechanism designs (Liu et al. 2017, b).
Beyond the stretchability, the conformability is important for the design of the soft HMIs. The soft HMIs should follow the motion of the soft skin surface for more accurate bio-potential signal recordings. Figure 3b depicted that the soft devices contact with the skin surface conformally for reducing motion artifacts (Jeong et al. 2013; Dong et al. 2017). Stretchable electronics with low bending stiffness and strong adhesion were able to promote conformal contact with human skin, and the criterion was designed for determining the conformability at the skin and soft electronics interface (Cheng, H.Y., Wang, S.D.: Mechanics of interfacial delamination in epidermal electronics systems. Journal of Applied Mechanics-Transactions of the Asme. 81 2014; Wang et al. 2012). In particular, conformability is key for high-performance functioning electronics in HMI applications.
The stability is another important factor for the design of soft HMIs. There were two buckling modes: out-of-surface buckling and in-surface buckling (Duan et al. 2014). The former affected the electrical performance as the stretchable interconnects would be detached from the substrate. The in-surface deformation interconnect was designed for stretchable electronics with thick bar geometries to yield scissor-like deformations modes as shown in Fig. 3c (Su et al. 2017; Su et al. 2015). It was still in surface during the stretching process with thick bar design methods.
3 Sensing from humans via HMIs
The sensing information to human bodies via the soft HMIs are divided into several categories: (1) soft tactile sensor; (2) motion sensors; and (3) electro-physiology sensors. The typical HMI modes based on these three kinds of sensors are reviewed.
3.1 Tactile sensors
Various soft tactile sensors have been designed and categorized by the functions such as pressure sensors, strain sensors and acoustic sensors. Pressure is one of the key physical parameter to evaluate the human sensing ability. Several kinds of pressure sensors have been designed for HMI applications, such as capacitive sensors (Mannsfeld et al. 2010), pressure sensitive rubber (PSR) sensors (Jung et al. 2014), piezoelectric pressure sensors, liquid metal sensors, and ionic gel sensors.
3.2 Motion sensors
Coordination and collaboration between humans and robots require motion sensing for complicated tasks. Soft sensors producing signals conforming to limb/joint rotations or soft-tissue deformations can be used to interpret human body motions from aspects of kinematics (angle, velocity and acceleration) (Menguc et al. 2014), kinetics (pressures and forces) (Trkov et al. 2017) and energy/power (muscle forces and deformations), which can be employed for motion intent recognition and robot control (Chen et al. 2013; Zheng et al. 2017).
3.3 Electrophysiology sensors
4 Feedback to humans
Stimulations based on soft tactile sensation from the physiology of the human skin to tactile sensing techniques have been studied in recent years. Several categories of stimulation to human bodies are designed, including electrotactile stimulation, sound and light stimulation, braille sheet display, and EEG-EMG biofeedback.
4.1 Electrotactile stimulation
Electrotactile stimulation evokes tactile sensations within the skin at the location of a small cutaneous electrode by passing a local electric current, through the skin to stimulate cutaneous afferent fibers. An electrocutaneous display system composed of three layers was implemented for the augmentation of skin sensation, where visual images captured by the sensor were translated into tactile information and displayed through electrotactile stimulation (Kajimoto et al. 2003). Integrating distributed sensing (E-skin) and stimulation (matrix electrodes), an electrotactile feedback system was proposed in Ref. (Franceschi et al. 2016) that helped user subjected to recognize dynamic movement patterns. It embodies closed-loop artificial devices into the user body scheme.
4.2 Sound and light stimulation
Sound and light stimulation to the human body is helpful to people’s therapy. The visual stimulation occurs through strobe lights, while auditory stimulation is made by binaural beats. The brain stimulation by light and sound between the biofeedback techniques was pushed forward by Calomeni et al. (Calomeni et al. 2013). Vieira defined the biofeedback as an immediate return of information through sensitive electronic equipment capable of capturing sensory responses, amplifying and transforming physiological signals (Vieira et al. 2007). The synthesis of brain waves fitted the definition well because the technology was able to stimulate the brain externally. Photo stimulation that highly corroborated with the possibility of brain waves could be induced through externally stimulated frequencies. The frequencies changed the state of consciousness depending on external factors such as time of stimulation, culture, and expectations of the individual (Budzynski 2009).
4.3 Electroactive polymer actuator for braille sheet display
The soft pneumatic actuators based on composites consists of flexible elastomers with embedded sheets or fiber structures which are inexpensive, simple to fabricate, light in weight, and easy to actuate (Wei et al. 2017; Gu et al. 2017). These soft pneumatic actuators could manipulate objects with moderate performance which they can lift loads up to 120 times their weight (Martinez et al. 2012; Bishop-Moser and Kota 2017). Soft robots were essentially more compatible for human interactions as their soft and easily deformable bodies ensured a minimal damage and load exerted to humans and environment (Lee et al. 2017). Soft robots with ability to adapt the curved and irregular surfaces allowed overcoming the shortcomings of rigid robots (Polygerinos et al. 2017). Soft robotic glove for hand rehabilitation performed specific tasks for training. There were many other works on hand rehabilitation by soft exoskeleton systems (Menguc et al. 2013). Embedded with nickel nanostructured microparticles, a organic polymer performed mechanical and electrical self-healing properties at ambient conditions, and it was pressure- and flexion-sensitive, and therefore suitable for electronic skin applications in soft robotics and biomimetic prostheses (Tee et al. 2012).
4.4 EEG-EMG biofeedback to human bodies
Figure 21c depicted that the closed-loop system could facilitate functional neuroplastic prosthesis and eventually elicit a joint brain and muscle motor rehabilitation (Sarasola-Sanz et al. 2017). Its usability was validated during a real-time operation session in a healthy participant and a chronic stroke patient, showing encouraging results for its application to a clinical rehabilitation scenario. The calibration session was divided into an EEG screening and an EMG calibration. The EMG calibration was performed with the healthy upper limb. Information from different aspects with multiple methods about the process of EEG-EMG signals and modeling of human motion was extracted and recognized. Generally speaking, HMI based on EEG-EMG biofeedback was an effective media to establish natural connections between humans and robots.
Figure 22b depicted a multi-pad electrode based functional electrical stimulation system for restoration of grasping. Since patients with low-level hemiplegia retained partial volitional muscle contraction ability, researchers attempted to extract information from muscle activities that remained under voluntary control sufficient to predict appropriate stimulation levels for several paralyzed muscles in the upper extremity (Malešević et al. 2012). Considering the difficulties of producing enough joint torque and dynamic control by using FES alone, EMG-driven electromechanical robot system integrated with FES was developed for wrist training after stroke. The performance of the system in assisting wrist flexion/extension tracking was evaluated on five chronic stroke subjects, which showed the FES-robot assisted wrist training could enhance the hand, wrist, and elbow functions.
5 Conclusion and discussion
This paper has highlighted the development of soft HMIs based on flexible and stretchable electronics technologies, including flexible/stretchable tactile sensors, motion sensors, biological sensors, and stimulation feedback to human bodies. Soft HMIs will play a key role in human-centered applications including robotics, sports, automobiles, textiles, and many other fields. Flexible/stretchable motion sensors are critically important for the robot and humans to accomplish complicated and dynamic tasks. Electrophysiology sensors have been developed as HMIs for EMG, ECG, and EOG signal recordings. The flexible electronic devices can stimulate human bodies for enhancing manual ability. Highly integrated electronics for the detection of multiple stimuli are the subject of many investigations. With the aid of newly emerging technologies, such as wireless sensor networks and ultrathin sensors, these efforts have received substantial attention in the field of health monitoring, medical implant services, and HMIs.
Recent developments in material science, nanotechnology, micro-/nano-fabrication techniques can improve HMI technologies in terms of performance, reliability, and miniaturization. (1) Conformal HMIs are designed and fabricated with flexible and stretchable electronics to provide a more friendly interface between human bodies and machines. Artificial skins with tactile sensors designed to mimic human skin in structural, functional, physiological and mechanical attributes, are promising in HMI applications. Flexible electronic devices have been used in many applications in recent tactile sensing technologies for their biocompatibility and excellent mechanical properties. (2) Soft tactile and bio-potential sensors are developed to improve human body rehabilitation as one type of HMIs, where flexile and stretchable electronics can be connected to a human nerve as part of human body. Stimulations to human bodies are generated by feedback information from the soft electronic devices integrated with soft tactile sensors or bio-potential sensors. (3) Soft HMIs promote interdisciplinary researches, such as flexible hybrid electronic manufacturing in the range of physics, material science, chemistry, informatics, manufacturing and so on. It would give an effective solution to fully flexible systems with soft sensors, soft printed circuit boards, and soft processors for improving the biocompatibility with human bodies.
However, there still exists some difficulties for the development of soft HMIs in the field of service robot and healthcare: (1) High manufacturing cost of soft HMIs among the critical issues to be considered in development. The low-cost materials and simple fabrication processes are desired to reduce cost. In a similar way, devices with low-power consumption or self-powering ability are worthy of in-depth studies. (2) More advanced intelligent sensing and congestive technologies are needed. Very large information and data must be exchanged between the human and machine for interacting more effectively. New algorithms are required for recognizing sensor signals to improve the communication and interaction efficiency, by mimicking real human skin which can adjust and provide feedback in real time according to the different types of external stimuli via the peripheral nervous systems. Future HMIs will also intelligently respond to variations in the external environment based on novel information transmission technology. (3) Coexistence safety could be a problem between the humans and machines. Multi-sensory and intelligent electronic devices should be thoroughly studied for future HMI applications, such as Tri-Co Robots. This provides an effective means for humans to interact with robots or machines in a similar way as human-to-human interactions. So soft HMIs provide a promising solution for a safe and friendly interaction between humans and robots.
The authors would like to acknowledge supports from the National Natural Science Foundation of China (51635007, 91748113, 51575412), Program for HUST Academic Frontier Youth Team, Special Project of Technology Innovation of Hubei Province. (2017AAA002), and State Key Lab of Digital Manufacturing Equipment & Technology, China (DMETKF2017003). The authors would like to thank Flexible Electronics Manufacturing Laboratory in Comprehensive Experiment Center for Advanced Manufacturing and Equipment Technology.
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