###### Abstract
An ultra-wideband (UWB) monopole-sensing antenna was designed on a flexible substrate and printed using the fuse-based filament method [10]. Another paper reports a new radio frequency identification (RFID) tag was printed on a cotton fabric using graphene ink via an nScrypt 3D-DW dispensing system [11]. The recent progress in flexible electronic systems, which utilises transistor-based circuitry and active-matrix technology built on plastics or textile substrates, has been extensively reviewed [12]. The focus lies on fabrication techniques using conventional materials that are commonly used in electronics. These flexible systems have paved the way for the development of various wearable sensor devices, including fattoo-based and biofluidic prototypes. These sensors have found applications in healthcare, particularly in WBAN systems [13]. Figure 1: Examples of technologies used in WBAN systems. However, there has been a significant surge in the development of sensing systems for industrial electronics. These sensing devices have undergone design, prototyping, and testing processes in both laboratory and real-life scenarios [14]. To cater to different electrical, mechanical, and thermal requirements, a wide range of flexible sensor devices has been developed using materials such as rigid, flexible, liquid, and single-crystal silicon, as well as a variety of polymers and nanomaterials, such as polydimethylsiloxane (PDMS), polyethylene terephthalate (PET), polyimide (PI), and polyethylene-naphthalene (PEN). Several flexible sensor devices have been designed using conductive polymer types of nanocomposite materials, such as poly (3_A_-ethylene dioxythiophene), polystyrene sulfonate (PEDOT: PSS), and polyaniline. In addition, carbon-based allotropes have been employed as processed materials to design wearable and flexible sensor devices [15]. A new stretching-insensitive bending sensor was designed and tested in [16]. A thin, porous PDMS sponge with a CNT network coating (CCPPS), which is flexible and bending-insensitive, was integrated with two electrodes to monitor the human body [17]. To support or use soft active materials such as carbon, metal, ion, or liquid metals, researchers have reported using flexible/stretchable non-active materials, which are discussed in [18], such as a small contact-lens platform that can be used for various human-machine interactions (HMI) [19]. Several human movements are sensed by shoe-mounted wearable sensors, which may be used for various purposes, including activity detection and energy expenditure estimation [20]. A disposable, ultrathin multi-layer adhesive patch with electrodes and interconnects for skin interfacing based on an Ag-In-Ga-filled elastomer was digitally produced and reported [21]. Nanomaterials have made it possible to develop tactile sensors that are well-suited for applications involving body parts such as skin. However, these sensors often encounter issues with a noisy environment and low power signals, which may contain contaminated data. The presence of noise can hinder the accurate collection of relevant information. Considering this, researchers have suggested the adoption of signal-processing methods based on neural networks (NNs) to improve the signal-to-noise ratio (SNR) and improve signal accuracy. Such approaches can help mitigate the impact of noise and enhance the reliability and accuracy of the collected data [22]. An advancement in machine learning combined with wearable technologies has revolutionised medical monitoring and human-machine interaction (HMI) by leveraging the following four key bio signals: electrocardiograms (ECGs), electromyography (EMG), electroencephalography (EEG), and photoplethysmography (PPG). ECG, when integrated with machine learning, enables accurate disease detection, heartbeat classification, and real-time cardiac monitoring, enhancing cardiac healthcare and identifying conditions like sleep apnea and stroke risk.