Data availability
Data supporting the findings of this study are available at Zenodo (https://doi.org/10.5281/zenodo.13874664)52. Source data are provided with this paper.
Code availability
Code supporting the findings of this study is publicly available at Zenodo (https://doi.org/10.5281/zenodo.13874664)52, except for code that, pursuant to copyright by Analog Devices, Inc. and Dialog Semiconductor Plc (‘vendors’), is not licenced for sharing. However, in most cases, such code is available for direct download from the vendors and has been annotated accordingly in our repository. Full code repositories are available from the corresponding author upon reasonable request and with permission of the vendors, as applicable.
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Acknowledgements
This study was sponsored by the Army Research Office and was accomplished under Cooperative Agreement Nos. W911NF-18-2-0048 and W911NF-23-2-0121. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Office of the US Government. The US Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein. We acknowledge the support from DTRA (Award No. HDTRA1-20-2-0002) Interaction of Ionizing Radiation with Matter University Research Alliance. S.P. acknowledges the support from the NSF Graduate Research Fellowship Program, the Fannie and John Hertz Foundation Fellowship, the Paul & Daisy Soros Foundation Fellowship for New Americans, the Knight-Hennessy Scholars Program at Stanford University and the Astronaut Scholarship Foundation. We thank K. Mazaheri, O. Schirm and S. Gupta for their contributions to the code implementation. We also thank A. Missakian for her support, inspiration and encouragement.
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Extended data figures and tables
Extended Data Fig. 1 Flexible Interposer Method for Device Packaging.
a. Images of the components placed on their corresponding interposers. b. Images showing examples of the workflow for the device packaging process for the microcontroller, with the device soldered onto the topside of the interposer with an auxiliary non-foldable region for initial programming (left), which is then cut down to the size of the device (central), and then folded around the device such that the contact pads on the bottom side of the interposer align with each of the faces of the device (right).
Extended Data Fig. 2 Pre-Connection Draw Process.
a. Images of devices pre-connected on an I2C bus on a spool, with 4 helically-wrapped wires for the intra-fibre communication protocol, and one guide wire for holding the tension of the draw. b. Image of preform with PMMA cladding encasing hollow ECOC cylinder. c. Image of a bare ECOC fibre after the PMMA cladding has been removed, with a microcontroller (MCU), accelerometer (acc), temperature sensor (temp), light sensor (LS), light emitting diode (LED), low dropout regulator (LDO), PPG sensor, and BLE module embedded inside the fibre.
Extended Data Fig. 3 Fibre Microscope Images.
Images of a a. microcontroller, b. LED, c. light sensor, d. temperature sensor, e. PPG sensor, f. accelerometer, g. low-dropout voltage regulator, h. BLE device, and i. Li-ion battery embedded in fibre. j. Closer-up image of the helical structure of the I2C conductors in the fibre.
Extended Data Fig. 4 Fatigue Testing.
Tensile fatigue testing of the fibre computer under different conditions. In each measurement, the resistance includes the four I2C wires and guide wire measured in parallel. a. Tensile fatigue testing between 0% and 5% strain at a strain rate of 1 Hz for a section of fibre with an embedded device. Failure in the first I2C wire occurs at 1697 cycles. b. Tensile fatigue testing between 0% and 15% strain at a strain rate of 0.2 Hz, for a section of fibre with an embedded device in the centre. Failure in the first I2C wire occurs at 122 cycles. c. Tensile fatigue testing between 0% and 15% strain at a strain rate of 0.2 Hz, for a section of fibre without an embedded device. Failure in the first I2C wire occurs at 542 cycles. d. Force-displacement curves during the first two cycles of fatigue testing of the section of fibre with the embedded device, showing the difference in tensile properties after the strain-limiting wire breaks during the first cycle.
Extended Data Fig. 5 Washability.
a. Images of a fibre computer embedded with a microcontroller, accelerometer, and BLE device undergoing 10 wash cycles. b. Status of the fibre before washing, with the I2C communications allowing for data exchange between the microcontroller and accelerometer, and the on-board LEDs of the microcontroller (red) and BLE (blue) devices indicating that the fibre is functional. Sensors are read at a polling rate of 50 Hz (20 ms between queries), while each sensor read takes 0.3 ms. c. Status of the fibre after washing, where we see the I2C communications between the microcontroller and accelerometer still intact to allow for data exchange, and the on-board LEDs of the microcontroller and BLE devices still indicating fibre functionality.
Extended Data Fig. 6 Tensile Properties of Braided Fibre Computers.
Images of fibre computers braided by a 16-carrier braiding machine using a. 540 denier polyester yarn and b. 360 denier cotton yarn, with 8 devices embedded inside each fibre. Enlarged image of a section of the c. polyester-braided and d. cotton-braided fibre containing an embedded microcontroller e. Force displacement curves for the braided fibre computers, with a notable enhancement in the tensile strength compared to bare fibres.
Extended Data Fig. 7 Optical Transmission Over Waveguide.
a. Images of the setup used for testing optical transmission over waveguide with controlled compression at the interface between the waveguide and fibres. A light sensor and LED fibre are placed a certain distance apart with a waveguide placed perpendicularly on top of the fibres. A screw-in clamp with an in-line load cell is used for adjusting the compressive strain and measuring the compressive force (Supplementary Note 9). In between the fibres, the waveguide is woven in a fabric to simulate the fabric environment. b. Increase in intensity received by the light sensor fibre over time as the compressive strain at the interface between the waveguide and LED fibre is increased in a stepwise manner. c. Amplitude received by the light sensor fibre when the LED fibre is excited with a square wave of different frequencies, showing a 3 dB bandwidth of between 10-20 kHz.
Extended Data Fig. 8 Implementation of Bluetooth Network for Distributed Inference.
a. Schematic showing the timeline of data transmission between fibres, with individual neural network inferences sent to a single fibre (left), which are then averaged to produce a network inference that is sent to another fibre (middle), which is then relayed to an external BLE display for continual monitoring. b. Image of four fibres, each with microcontrollers (red) and BLE modules (blue) for wireless communication of neural network inference between fibres. c. Example image of inference output on an external phone display communicated via BLE from four-fibre network.
Extended Data Fig. 9 In-Fabric Optical Communications.
a. Images of the interfaces between the LED fibre and waveguides (top left), and the light sensor fibre and waveguides (bottom left) for the sample with lower tension. Image of sample when the LED fibre is emitting light, showing weak coupling to the waveguide bus (right). b. Images of the interfaces between the LED fibre and waveguides (top left), and the light sensor fibre and waveguides (bottom left) for the sample with higher tension. Image of sample when the LED fibre is emitting light, showing stronger coupling to the waveguide bus (right). c. Plot of the intensity received by the light sensor in each fabric when the LED fibre is toggled to the on state. The distance between the LED fibre and light sensor fibre is 3 cm in each case. d. Bit transmission at 5 Hz in the fabric sample shown in (b), where the LED and light sensor fibres are separated by 7.5 cm.
Extended Data Fig. 10 Extraction of Weights for Pre-Encoding Anatomical Behavioural Awareness.
An example of the process for extracting the confidence level weights that were pre-encoded on the individual fibres for performing the federated inference algorithm with anatomical behavioural awareness (Supplementary Note 11). a. The validation set confusion matrix for the right leg fibre, with the precision of the predictions for each activity listed below. The precisions from each limb’s fibre on the validation dataset were pre-stored in a corresponding array on each fibre to enable evaluation of the federated inference algorithm evaluation on the test dataset. b. The arrays of confidence weights stored on each fibre.
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The supplementary information file contains Supplementary Notes 1–12, Figs. 1–13, Tables 1 and 2 and References.
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Gupta, N., Cheung, H., Payra, S. et al. A single-fibre computer enables textile networks and distributed inference. Nature 639, 79–86 (2025). https://doi.org/10.1038/s41586-024-08568-6
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DOI: https://doi.org/10.1038/s41586-024-08568-6