## 4 Overview of Wearable Interface for Providing Haptic Feedback
The sensing mechanism is based on the interaction between the finger skin, which serves as a positive triboelectric element, and the elastomer, acting as a negative element. A microcontroller generates a pulse-width modulation (PWM) signal for activating the vibrating actuator. The device's size may be decreased when Smore DOFs can be detected. Machine learning provides an appealing approach for in-depth analysis of the observed triboelectric signals and extracting useful patterns from various occurrences [60; 61],  
Figure 8: Vi-Hab system with highlighted main components: the wearable band and 5 vibrating motors [56]; a force sensitive resistors (FSR) and related motor are present for each finger of the dummy hand (from 1 to 5, totally five). The wearable band (in the inset) wraps around the upper arm such that each motor falls in line with the natural position of the fingers as shown by the red arrows. Figure 9: Glove-based HMI for general purposes; it includes (**a**) triboelectric finger sensors for sensing bending movements (**b**) with a related operating principle (**c**), a triboelectric palm sensor (**c**) for detecting the sliding movements (**d**) with a related operating principle (**e**), and piezoelectric mechanical stimulator for generating haptic feedback (**f**) [34]. enabling the alternative implementation of the presented smart glove with significantly fewer sensors. Sixteen sensors integrated into the smart glove were simultaneously monitored as a preliminary test [62; 63]. To give adequate characteristics for their study, the authors aggregated the dataset from sixteen channels to extract the required features [60]. Convolutional neural networks (CNN) are a great tool to extract features automatically and simultaneously decrease data complexity. The confusion map of the models demonstrates that both approaches may help the glove achieve above 96% recognition accuracy using 400 training data for every item. Now, arguing on a different design strategy, several recent studies focused on improving users' orientation and positioning perceptions when using haptic devices. According to their force reference system, tactile devices employed for this purpose may be divided into three categories: grounded, body grounded, and ungrounded [64]. These technologies have a wide range of uses, from personal assistants for visually impaired individuals [65] to teleoperation, particularly in the fields of micro-robotics [66], medicine, and training using emulators [67; 68]. Therefore, one strategy to enhance these impressions is to employ haptics to deliver feedback. [PERSON] et al. suggested employing piezoelectric actuators to meet these requirements (Figure 10). In their work, a novel ungrounded haptic device was created, examined, and experimentally validated. The unique gadget creates an illusion of force using asymmetric accelerations and a piezo-actuator. Experimental evaluations are performed to ascertain the force produced by the device and verify the user's impression [69]. The presented tactile system is made up of an aluminum frame, a linear guideway, a brass moving component, and a piezo actuator, which drives the mobile component (Figure 10). Three-axis accelerometers monitor the acceleration of both the mobile item and the framework. The research is based on [PERSON]'s haptic principle, a method that relies on a pseudo-attraction force produced by unbalanced accelerations [70; 71; 72; 73]. An innovative method to improve orientation for users who are blind or visually challenged users, or in other contexts such as simulators, is using portable haptic devices. There are several existing methods; however, they all primarily concentrate on reducing volume and force. As a result, systems that offer both a compact size and the development of strong forces are required. The haptic feedback mechanism can be considered a combination of acoustic radiation force and acoustic streaming.