## 4 Dynamic Assessment of Movement Performance
### Wearable Pressure Sensors  
Pressure sensors are measuring devices for the contact area and force test. The principle of pressure sensors, piezoresistive, capacitive, and piezoelectric, is like that of strain sensors. Usually, a pressure sensor consists of an electrode layer exploited to transmit signals and an active one that deforms under the action of the pressure and causes voltage changes in the output signal [82]. The most widespread application of pressure sensors is the monitoring of plantar pressure during walking and sports, integrating it directly into the insole of a shoe. This aspect constitutes a critical path to assess the gait of the subjects examined. Various gait variables during sport were obtained through these sensors, including plantar pressure (peak/average pressure), reaction force, and center of pressure (CoP) [82]. Foot pressure measurement is also essential in healthcare applications, clinical rehabilitation, and pedestrian navigation. In recent studies, nanotube-based pressure sensors/polydimethylsiloxane have been used to monitor it [83]. Integrated low-cost strain and pressure sensor systems were also used to measure wrist movements and obtained at low cost and with a simple production process. This time, the resistive bending strain sensor in the system was manufactured by polyimide sintering. In contrast, the resistive pressure sensor was implemented based on a composite structure of silver nanowires and expandable pressure sensors/polydimethylsiloxane microspheres with adjustable sensitivity and operation range. This system has shown great application potential in motion monitoring and intelligent human-machine interfaces [84]. Smart Insoles in Human Gait and Posture Analysis  
Gait insoles are widely utilized for gait analysis, highlighting possible motion dysfunctions in healthy subjects or incorrect patterns in people with gait impairments. Indeed, real-time gait analysis represents a key factor in improving rehabilitation devices. Smart insoles have been studied for many years, producing increasingly simple and highly effective models, which may reduce the issue of uncomfortable wearable devices within the shoes. Foot pressure detection is fundamental in recording data on people's dynamic movement and posture [85] since the foot represents the first body point of contact with the ground and gives information on the world around [86]. Due to this, data records on foot pressure are essential to develop novel kinds of sensors (Figure 4). Figure 4: Insole outline of the recording and data analysis of smart insoles. Piezoresistive, photoelectric, 6-axis, pressure, and flex sensors were used in the reported studies. The number and position of sensor units changed concerning the author’s decision. Furthermore, the most relevant analyzed gait parameters are velocity, stride time, CoP, step count, and phase coordination index [87, 88, 89, 90, 91]. Ref. [86] developed a couple of insole models based on photoelectric sensing unit functioning, each composed of six-unit sensors capable of recording data on foot pressure, produced with cheap materials (elastic silicone). The authors proposed a test for moving from a natural standing to walking and returning to a standing position. The gait analysis outcomes were dependable, but the connecting cables represented the principal limit of such insoles to the device. Indeed, the cable could lead to impediment and discomfort during walking time, suggesting the need to produce a wireless model. Ref. [86] presented a soft-material-based smart insole, which is light, durable, and wirelessly connected. The authors compared this proposed novel device to a commercial in-shoe cables-connected sensor to assess its performance. The tests performed simultaneously wearing both sensors and carried out at different walking velocities showed a full correlation between the two devices. The values recorded in this study led to comparable outcomes between the proposed wireless soft smart insole and the other cable-connected sensors. Ref.