## 6 Designed Architecture of the Smart Sensory Glove Based on AlN-Based Sensors
First, the sensor was inserted in a chamber where controlled pulsed air flows were generated, resulting in pressure on the sensor surface between 10 kPa and 50 kPa measured using a pull shear apparatus. Then, the voltage signal was taken and measured directly from the sensor, without any intermediate filtering or amplification stage, finding good linearity between the open-circuit voltage signal and the applied pressure, according to the following equation:  
\[\mathrm{V_{piezo}}=\alpha\mathrm{A_{contact}P} \tag{5}\]  
where the \(\alpha\) parameter is a function of the intrinsic material properties and its response to mechanical deformations, \(\mathrm{A_{contact}}\) is the sensor's contact surface, and \(\mathrm{P}\) is the applied pressure. Within the examined pressure interval, a 0.025 V/N sensitivity and a 15 \(\pm\) 2 ms response time (the rise time between 10% and 90% of the signal) were calculated. Specifically, the smart glove is constituted by a standard cotton glove on which five custom piezoelectric sensors are placed at the knuckles of the fingers by silicone glue. These sensors allow the discrete detection of finger movements, given their very low thickness and weight and high flexibility. A similar application of AlN-based piezo-tribo sensors was proposed in [22], in which they were tested for their ability to detect different body movements, including hand gestures (Figure 19). This study introduces a wearable hybrid sensor (WHS) with three inorganic/elastomeric electrodes for multifunctional and multi-site identification of human movements. The piezoelectric component is based on the same stack previously presented in Figure 18, which was coupled with a conformable triboelectric component consisting of a PDMS and Ecoflex blend and encapsulated a parylene C layer, whose surface was modified with UV/ozone and oxygen plasma. In this paper, we perform a step forward in terms of integration and data processing compared to the idea presented in [22]. Figure 18: Illustration of the different layers constituting the sensor, and in the box, the representation of the connection package made by 3D printing **(a)**. Illustration of the sensor’s shape and dimensions **(b)**. Photograph of the resulting sensor connected with a coaxial cable **(c)**[20]. The tiny signals generated by the five sensors must be amplified and conditioned before being acquired by the following acquisition section. In laboratories, professional and specialized equipment is used to acquire and process the piezoelectric output voltage from sensors; however, realizing an electronic acquisition and amplification board is quite simple and allows almost the same performances to be obtained at lower costs and dimensions. Additionally, to ensure better comfort, the smart glove should integrate a stage to amplify  
Figure 19: The detection of hand motions using the developed WHSs. (**A**) Five sensors are attached to the back of a human hand in positioning scheme (i) and picture (ii). A detected signal corresponding to the hyperextension of the index finger (iii). (**B**) The signal provided by WHS applied to the middle finger for different hand apertures. (**C,D**) The detected signals generated by five WHSs at the hand’s rear, starting from the closed (**C**) or the open (**D**) hand, for various conditions: distended index finger (i), index and middle finger (ii); thumb, index, and middle finger (iii); all fingers except for the pinkie (iv); all fingers (v). (**E**) A series of actions involving the thumb and pinkie that begin with the closed hand. (**F**) The reliability measurement obtained during 100 repetitions of the closed-opened hand. The measurements were carried out by applying the WHSs on the middle finger and pinkie. and filter the signals generated by the piezoelectric transducers and then acquire and process them to extract useful information.