The task of determining the physical coordinates of a target in indoor environments is still a key factor for many applications including people and robot navigation, user tracking, location-based advertising, augmented reality, gaming, emergency response or ambient assisted living environments. Among the different possibilities for indoor positioning, Acoustic Local Positioning Systems (ALPS) have the potential for centimeter level positioning accuracy with coverage distances up to tens of meters. In addition, acoustic transducers are small, low cost and reliable thanks to the room constrained propagation of these mechanical waves. Waveform design (coding and modulation) is usually incorporated into these systems to facilitate the detection of the transmitted signals at the receiver. The aperiodic correlation properties of the emitted signals have a large impact on how the ALPS cope with common impairment factors such as multipath propagation, multiple access interference, Doppler shifting, near-far effect or ambient noise. This work analyzes three of the most promising families of codes found in the literature for ALPS: Kasami codes, Zadoff-Chu and Orthogonal Chirp signals. The performance of these codes is evaluated in terms of time of arrival accuracy and characterized by means of model simulation under realistic conditions and by means of experimental tests in controlled environments. The results derived from this study can be of interest for other applications based on spreading sequences, such as underwater acoustic systems, ultrasonic imaging or even Code Division Multiple Access (CDMA) communications systems.

This work presents the CODEUS platform, which includes a simulation tool together with an online experimental demonstrator to offer analysis and testing flexibility for researchers and developers in Ultrasonic Indoor Positioning Systems (UIPSs). The simulation platform allows most common encoding techniques and sequences to be tested in a configurable UIPS. It models the signal modulation and processing, the ultrasonic transducers’ response, the beacon distribution, the channel propagation effects, the synchronism, and the application of different positioning algorithms. CODEUS provides results and performance analysis for different metrics and at different stages of the signal processing. The UIPS simulation tool is specified by means of the MATLAB© App-Designer environment, which enables the definition of a user-friendly interface. It has also been linked to an online demonstrator that can be managed remotely by means of a website, thus avoiding any hardware requirement or equipment on behalf of researchers. This demonstrator allows the selected transmission schemes, modulation or encoding techniques to be validated in a real UIPS, therefore enabling a fast and easy way of carrying out experimental tests in a laboratory environment, while avoiding the time-consuming tasks related to electronic design and prototyping in the UIPS field. Both simulator and online demonstrator are freely available for researchers and students through the corresponding website.

Ultrasonic Local Positioning Systems (U-LPS) can be used for fine-grained indoor positioning. Typically, multiple fixed beacons simultaneously emit ultrasonic signals whose time of arrival is estimated at a mobile receiver. The ultrasonic signals are encoded and modulated to allow separation of the signals at the receiver, identification of the transmitters, and mitigation of signal impairments such as multipath, the near-far effect, multiple access interference, and Doppler shift. Hence, waveform design (coding and modulation) plays a pivotal role in determining the performance of such a system. This paper compares the performance of four modulation techniques (specifically QPSK, OFDM, Slow-FHSS and Fast-FUSS) transmitting Zadoff-Chu (ZC) sequences in an U-LPS. The modulation schemes are evaluated in terms of time of arrival accuracy and positioning accuracy in simulation and real-world experiments. Simulation and, to a lesser extent, real-world tests indicate that ZC coded QPSK modulation with non-coherent detection using a matched filter, offers greater accuracy under realistic conditions than the other modulation schemes.

Electromyography (EMG) signals are fundamental in neurorehabilitation as they provide a non-invasive means of capturing the electrical activity of muscles, enabling precise detection of motor intentions. This capability is essential for controlling assistive devices, such as therapeutic exoskeletons, that aim to restore mobility and improve motor function in patients with neuromuscular impairments. The integration of EMG into neurorehabilitation systems allows for adaptive and patient-specific interventions, addressing the variability in motor recovery needs. However, achieving the high fidelity, low latency, and robustness required for real-time control of these devices remains a significant challenge. This paper introduces a novel multi-channel electromyography (EMG) acquisition system implemented on a System-on-Chip (SoC) architecture for robotic neurorehabilitation. The system employs the Zynq-7000 SoC, which integrates an Advanced RISC Machine (ARM) processor, for high-level control and an FPGA for real-time signal processing. The architecture enables precise synchronization of up to eight EMG channels, leveraging high-speed analog-to-digital conversion and advanced filtering techniques implemented directly at the measurement site. By performing filtering and initial signal processing locally, prior to transmission to other subsystems, the system minimizes noise both through optimized processing and by reducing the distance to the muscle, thereby significantly enhancing the signal-to-noise ratio (SNR). A dedicated communication interface ensures low-latency data transfer to external controllers, crucial for adaptive control loops in exoskeletal applications. Experimental results validate the system’s capability to deliver high signal fidelity and low processing delays, outperforming commercial alternatives in terms of flexibility and scalability. This implementation provides a robust foundation for real-time bio-signal processing, advancing the integration of EMG-based control in neurorehabilitation devices.

Complementary Set of Sequences (CSS) are being widely used in communications due to the ideal correlation properties and the availability of efficient correlators that significantly reduce the number of computations in the detection process. In this paper, the performance of the acoustic signals encoded by multilevel CSS in an underwater horizontal link is analysed. For that, a channel propagation model based on ray tracing is used, where parameters for the San Jorge Gulf Argentina are included. The main goal of this is to analyse the transmission scheme based on acoustic encoded signals, in order to be used in a communication system, between a buoy in a surface and a group of sensors on the seabed, that form a sensor network for coastal monitoring. Other application of this scheme can be a positioning system, where a set of sensors of the network are deployed on the seabed in order to compute its position. The obtained results show a suitable robustness of the used encoding scheme based on Multilevel Complementary Sets of Sequences in a point-to-point link in shallow water, where it is possible to detect encoded signals even under hard conditions of attenuation and SNR.