# Recent Advances in Fiber-Shaped Electronic Devices for Wearable Applications
## 3 Device Applications
### Electronic Devices
#### 3.1.3 Computing Units
Their fiber-shaped multi-synaptic device platform could independently address and transmit neural signals without undesired interference between individual synapses in an e-textile neural network [45]. The 1D artificial synapses were fabricated using P(VDF-TrFE) film dip-coated on a thin Ag wire [45]. They showed essential synaptic functions by modulating the degree of polarization through the electrical stimulus, and their device operated well under bent and coiled states, indicating excellent mechanical stability (Figure 4c) [45]. A NOR-type synaptic array was demonstrated by cross-connecting 1D multi-synapses and Ag fiber electrodes, and the output signals from the individual synapses could be integrated and propagated without significant leakage (Figure 4d) [45]. In particular, recognition accuracies of up to \(\sim\)90 and \(\sim\)70% were achieved for modified National Institute of Standards and Technology (MNIST) and electrocardiogram (ECG) patterns, respectively (Figure 4d) [45]. The initial accuracy  
Figure 4: (a) Schematic illustration of a DNA-bridged memristor and photograph of the integration of textile power supply, chip, and light-emitting modules for the textile chip. (b) Left: the basic logic-in-memory function of NAND. Right: photograph of a NAND logic operation in an all-fabric data-processing system. (a,b) Reproduced with permission Ref. [41]. Copyright 2020, Wiley-VCH. (c) Left: schematic illustration of fiber-shaped organic artificial synapses. Right: repetitive transitions of the LTP/LTD of postsynaptic response current (\(I_{PSC}\)) at a fixed bending radius (\(R\) = 2.5 mm). (d) Left: plot of the integrated \(I_{PSC}\) in the 2 \(\times\) 2 array, with alternately applied current potentiating the two different voltage pulses, with \(\Delta t\) = 5 s at each preneuron. The inset is a photograph of the 2 \(\times\) 2 array. Right: recognition accuracy for MNIST patterns with respect to the number of learning epochs. The left inset presents a reshaped 28 \(\times\) 28 contour image of the digit 3 from \(w\) before and after 10 epochs, and the right inset shows the confusion matrix for a classification test involving 10,000 MNIST images after 10 epochs. (c,d) Reproduced with permission Ref. [45]. Copyright 2020, American Association for the Advancement of Science (AAAS). for the ECG pattern was almost maintained, even under 100 bending cycles at a fixed bending radius of 2.5 mm (error margin: \(\sim\)2%) [45]. The 1D multi-synapses built as a proof of concept provide a promising approach to the realization of an e-textile neural network for use in a wearable neuromorphic electronic system [45]. Clearly, developments and breakthroughs have been made in the structural designs and capabilities of fiber-shaped computing components. Although a neural textile network that can receive multi-terminal signals and build a high-density artificial neural system has been demonstrated, the processing efficiency should be increased, and fundamental synaptic functions should be accurately mimicked [42].