Search Results (13)

The integration of AI and robotics in healthcare raises concerns, and additional issues regarding autonomous systems are anticipated. Effective communication is crucial for robots to be seen as “caring”, necessitating advanced mechatronic design and natural language processing (NLP). This paper examines the potential of humanoid robots to autonomously replicate compassionate care. The study employs computational simulations using mathematical and agent-based modeling to analyze human–robot interactions (HRIs) surpassing Tetsuya Tanioka’s TRETON. It incorporates stochastic elements (through neuromorphic computing) and quantum-inspired concepts (through the lens of Martha Rogers’ theory), running simulations over 100 iterations to analyze complex behaviors. Multisensory simulations (visual and audio) demonstrate the significance of “dynamic communication”, (relational) “entanglement”, and (healthcare system and robot’s function) “superpositioning” in HRIs. Quantum and neuromorphic computing may enable humanoid robots to empathetically respond to human emotions, based on Jean Watson’s ten caritas processes for creating transpersonal states. Autonomous AI humanoid robots will redefine the norms of “caring”. Establishing “pluralistic agreements” through open discussions among stakeholders worldwide is necessary to align innovations with the values of compassionate care within a “posthumanist” framework, where the compassionate care provided by Level 4 robots meets human expectations. Achieving compassionate care with autonomous AI humanoid robots involves translating nursing, communication, computer science, and engineering concepts into robotic care representations while considering ethical discourses through collaborative efforts. Nurses should lead the design and implementation of AI and robots guided by “technological knowing” in Rozzano Locsin’s TCCN theory. Full article

Research of novel biosignal modalities with application to remote patient monitoring is a subject of state-of-the-art developments. This study is focused on sonified ECG modality, which can be transmitted as an acoustic wave and received by GSM (Global System for Mobile Communications) microphones. Thus, the wireless connection between the patient module and the cloud server can be provided over an audio channel, such as a standard telephone call or audio message. Patients, especially the elderly or visually impaired, can benefit from ECG sonification because the wireless interface is readily available, facilitating the communication and transmission of secure ECG data from the patient monitoring device to the remote server. The aim of this study is to develop an AI-driven algorithm for 12-lead ECG sonification to support diagnostic reliability in the signal processing chain of the audio ECG stream. Our methods present the design of two algorithms: (1) a transformer (ECG-to-Audio) based on the frequency modulation (FM) of eight independent ECG leads in the very low frequency band (300–2700 Hz); and (2) a transformer (Audio-to-ECG) based on a four-layer 1D convolutional neural network (CNN) to decode the audio ECG stream (10 s @ 11 kHz) to the original eight-lead ECG (10 s @ 250 Hz). The CNN model is trained in unsupervised regression mode, searching for the minimum error between the transformed and original ECG signals. The results are reported using the PTB-XL 12-lead ECG database (21,837 recordings), split 50:50 for training and test. The quality of FM-modulated ECG audio is monitored by short-time Fourier transform, and examples are illustrated in this paper and supplementary audio files. The errors of the reconstructed ECG are estimated by a popular ECG diagnostic toolbox. They are substantially low in all ECG leads: amplitude error (quartile range RMSE = 3–7 μV, PRD = 2–5.2%), QRS detector (Se, PPV > 99.7%), P-QRS-T fiducial points’ time deviation (<2 ms). Low errors generalized across diverse patients and arrhythmias are a testament to the efficacy of the developments. They support 12-lead ECG sonification as a wireless interface to provide reliable data for diagnostic measurements by automated tools or medical experts. Full article

Starting approximately from the beginning of the new millennium, a series of studies highlighted that auditory information deriving from biological motion can significantly influence the behavioral, cognitive and neurophysiological processes involved in the perception and execution of complex movements. In particular, it was observed that an appropriate use of sounds deriving from one’s own movement promotes improvements in the movement execution itself. Two main approaches can be used, namely the sonification one or the ecological sound one; the former is based on the conversion of physiological and/or physical movement data into sound, while the latter is based on the use of auditory recordings of movement sounds as models. In the present article, some of the main applications of both approaches—especially the latter—to the domains of sport and motor rehabilitation are reviewed, with the aim of addressing two questions: Is it possible to consider rhythm as a Gestalt of human movement? If so, is it possible to build up cognitive strategies to improve/standardize movement performance from this Gestalt? As with most topics in science, a definitive answer is not possible, yet the evidence leads us to lean toward a positive answer to both questions. Full article

This paper presents the design, development, and feasibility testing of a wearable sonification system for real-time posture monitoring and feedback. The system utilizes inexpensive motion sensors integrated into a compact, wearable package to measure body movements and standing balance continuously. The sensor data is processed through sonification algorithms to generate real-time auditory feedback cues indicating the user’s balance and posture. The system aims to improve movement awareness and physical conditioning, with potential applications in balance rehabilitation and physical therapy. Initial feasibility testing was conducted with a small group of healthy participants performing standing balance tasks with eyes open and closed. Results indicate that the real-time audio feedback improved participants’ ability to maintain balance, especially in the case of closed eyes. This preliminary study demonstrates the potential for wearable sonification systems to provide intuitive real-time feedback on posture and movement to improve motor skills and balance. Full article

An objective of chemical ecology is to understand the chemical diversity across and within species, as well as the bioactivity of chemical compounds. We previously studied defensive volatiles from phytophagous insects that were subjected to parameter mapping sonification. The created sounds contained information about the repellent bioactivity of the volatiles, such as the repellence from the volatiles themselves when tested against live predators. Here, we applied a similar sonification process to data about human olfactory thresholds. Randomized mapping conditions were used and a peak sound pressure, Lpeak, was calculated from each audio file. The results indicate that Lpeak values were significantly correlated with the olfactory threshold values (e.g., r_S = 0.72, t = 10.19, p < 0.001, Spearman rank-order correlation; standardized olfactory thresholds of 100 volatiles). Furthermore, multiple linear regressions used the olfactory threshold as a dependent variable. The regressions revealed that the molecular weight, the number of carbon and oxygen atoms, as well as the functional groups aldehyde, acid, and (remaining) double bond were significant determinants of the bioactivity, while the functional groups ester, ketone, and alcohol were not. We conclude that the presented sonification methodology that converts chemicals into sound data allows for the study of their bioactivities by integrating compound characteristics that are easily accessible. Full article

Three decades after the first set of work on Medical Augmented Reality (MAR) was presented to the international community, and ten years after the deployment of the first MAR solutions into operating rooms, its exact definition, basic components, systematic design, and validation still lack a detailed discussion. This paper defines the basic components of any Augmented Reality (AR) solution and extends them to exemplary Medical Augmented Reality Systems (MARS). We use some of the original MARS applications developed at the Chair for Computer Aided Medical Procedures and deployed into medical schools for teaching anatomy and into operating rooms for telemedicine and surgical guidance throughout the last decades to identify the corresponding basic components. In this regard, the paper is not discussing all past or existing solutions but only aims at defining the principle components and discussing the particular domain modeling for MAR and its design-development-validation process, and providing exemplary cases through the past in-house developments of such solutions. Full article

Background: Chemistry and biology students often have difficulty understanding molecular structures. Sonification (the rendition of data into non-speech sounds that convey information) can be used to support molecular understanding by complementing scientific visualization. A proper sonification design is important for its effective educational use. This paper describes a participatory design (PD) approach to designing and developing the sonification of a molecular structure model to be used in an educational setting. Methods: Biology, music, and computer science students and specialists designed a sonification of a model of an insulin molecule, following Spinuzzi’s PD methodology and involving evolutionary prototyping. The sonification was developed using open-source software tools used in digital music composition. Results and Conclusions: We tested our sonification played on a virtual reality headset with 15 computer science students. Questionnaire and observational results showed that multidisciplinary PD was useful and effective for developing an educational scientific sonification. PD allowed for speeding up and improving our sonification design and development. Making a usable (effective, efficient, and pleasant to use) sonification of molecular information requires the multidisciplinary participation of people with music, computer science, and molecular biology backgrounds. Full article

Objectives: This research aims to apply an auditory display for tumor imaging using fluorescence data, discuss its feasibility for in vivo tumor evaluation, and check its potential for assisting enhanced cancer perception. Methods: Xenografted mice underwent fluorescence imaging after an injection of cy5.5-glucose. Spectral information from the raw data was parametrized to emphasize the near-infrared fluorescence information, and the resulting parameters were mapped to control a sound synthesis engine in order to provide the auditory display. Drag–click maneuvers using in-house data navigation software-generated sound from regions of interest (ROIs) in vivo. Results: Four different representations of the auditory display were acquired per ROI: (1) audio spectrum, (2) waveform, (3) numerical signal-to-noise ratio (SNR), and (4) sound itself. SNRs were compared for statistical analysis. Compared with the no-tumor area, the tumor area produced sounds with a heterogeneous spectrum and waveform, and featured a higher SNR as well (3.63 ± 8.41 vs. 0.42 ± 0.085, p < 0.05). Sound from the tumor was perceived by the naked ear as high-timbred and unpleasant. Conclusions: By accentuating the specific tumor spectrum, auditory display of fluorescence imaging data can generate sound which helps the listener to detect and discriminate small tumorous conditions in living animals. Despite some practical limitations, it can aid in the translation of fluorescent images by facilitating information transfer to the clinician in in vivo tumor imaging. Full article

Feedback is one of the significant factors for the mental mapping of an environment. It is the communication of spatial information to blind people to perceive the surroundings. The assistive smartphone technologies deliver feedback for different activities using several feedback mediums, including voice, sonification and vibration. Researchers 0have proposed various solutions for conveying feedback messages to blind people using these mediums. Voice and sonification feedback are effective solutions to convey information. However, these solutions are not applicable in a noisy environment and may occupy the most important auditory sense. The privacy of a blind user can also be compromised with speech feedback. The vibration feedback could effectively be used as an alternative approach to these mediums. This paper proposes a real-time feedback system specifically designed for blind people to convey information to them based on vibration patterns. The proposed solution has been evaluated through an empirical study by collecting data from 24 blind people through a mixed-mode survey using a questionnaire. Results show the average recognition accuracy for 10 different vibration patterns are 90%, 82%, 75%, 87%, 65%, and 70%. Full article

Sonification is the utilization of sounds to convey information about data or events. There are two types of emotions associated with sounds: (1) “perceived” emotions, in which listeners recognize the emotions expressed by the sound, and (2) “induced” emotions, in which listeners feel emotions induced by the sound. Although listeners may widely agree on the perceived emotion for a given sound, they often do not agree about the induced emotion of a given sound, so it is difficult to model induced emotions. This paper describes the development of several machine and deep learning models that predict the perceived and induced emotions associated with certain sounds, and it analyzes and compares the accuracy of those predictions. The results revealed that models built for predicting perceived emotions are more accurate than ones built for predicting induced emotions. However, the gap in predictive power between such models can be narrowed substantially through the optimization of the machine and deep learning models. This research has several applications in automated configurations of hardware devices and their integration with software components in the context of the Internet of Things, for which security is of utmost importance. Full article

Stolen Voices is a research enquiry that uses listening as both methodology and material. Stolen Voices develops techniques for ‘listening in’ and eavesdropping to help articulate an epistemology of place through sonic frameworks. A core motivation for the listening is a semi-fictional story we tell ourselves (and anyone else who is listening): an ‘event’ has taken place along the East Coast of the United Kingdom (UK), and we have been tasked with figuring out what has happened. While the specifics of the event might be difficult to pin down, the urgency of the investigation is fuelled by concrete concerns found in the UK edgelands, at the border/margin of the country: the uncertain future of the UK’s relationship with Europe; the effects of climate change on coastal landscapes; the waning of industries like manufacturing and coal extraction; the oil industry in crisis; the rise of global shipping infrastructures. By using a semi-fictional framework, we move away from mapping techniques like data-sonification towards a methodology that embraces gaps and inventive excesses while insisting on the importance of making an account. Through listening, we foster attention to contingencies and indeterminacies and their relationships to prevailing structures and knowledge hierarchies. Stolen Voices asks: what is the relationship between a listener and what is heard? How can listening attune us to the complexities of contemporary political, economic, ecological and social processes? How did we get to where we are now, and how, through listening, can we seek out levers for change? What do the rhythms and atmospheres of specific geographic locations inform or reveal about history? Evolving over several years, in response to what we hear, the investigation necessarily proceeds slowly. In this article, we unfold our methodological processes for the detection of sound, voices, atmosphere and affect. We use creative-critical writing to evidence the construction of a research investigation focused on the act of listening as a spatial practice and necessarily collective endeavour. Full article

Urban traffic noise situations are usually visualized as conventional 2D maps or 3D scenes. These representations are indispensable tools to inform decision makers and citizens about issues of health, safety, and quality of life but require expert knowledge in order to be properly understood and put into context. The subjectivity of how we perceive noise as well as the inaccuracies in common noise calculation standards are rarely represented. We present a virtual reality application that seeks to offer an audiovisual glimpse into the background workings of one of these standards, by employing a multisensory, immersive analytics approach that allows users to interactively explore and listen to an approximate rendering of the data in the same environment that the noise simulation occurs in. In order for this approach to be useful, it should manage complicated noise level calculations in a real time environment and run on commodity low-cost VR hardware. In a prototypical implementation, we utilized simple VR interactions common to current mobile VR headsets and combined them with techniques from data visualization and sonification to allow users to explore road traffic noise in an immersive real-time urban environment. The noise levels were calculated over CityGML LoD2 building geometries, in accordance with Common Noise Assessment Methods in Europe (CNOSSOS-EU) sound propagation methods. Full article

The pattern of gait after hip arthroplasty strongly affects regeneration and quality of life. Acoustic feedback could be a supportive method for patients to improve their walking ability and to regain a symmetric and steady gait. In this study, a new gait sonification method with two different modes—real-time feedback (RTF) and instructive model sequences (IMS)—is presented. The impact of the method on gait symmetry and steadiness of 20 hip arthroplasty patients was investigated. Patients were either assigned to a sonification group (SG) (n = 10) or a control group (CG) (n = 10). All of them performed 10 gait training sessions (TS) lasting 20 min, in which kinematic data were measured using an inertial sensor system. Results demonstrate converging step lengths of the affected and unaffected leg over time in SG compared with a nearly parallel development of both legs in CG. Within the SG, a higher variability of stride length and stride time was found during the RTF training mode in comparison to the IMS mode. Therefore, the presented dual mode method provides the potential to support gait rehabilitation as well as home-based gait training of orthopedic patients with various restrictions. Full article