Sound Feedback Research Articles

Application of an Auditory-Based Feedback Distortion to Modify Gait Symmetry in Healthy Individuals.

Augmenting auditory feedback through an error-augmentation paradigm could facilitate the perception and correction of gait asymmetry in stroke survivors, but how such a paradigm should be tailored to individual asymmetry profiles remains unclear. Before implementing the paradigm in rehabilitation, we need to investigate the instantaneous effects of distorted footstep sound feedback on gait symmetry in healthy young adults. Participants (n = 12) walked on a self-paced treadmill while listening to their footstep sounds, which were distorted unilaterally according to five conditions presented randomly: small delay; small advance; large delay; large advance; or unmodified (control). The primary outcomes were swing time ratio (SWR) and step length ratio (SLR). Secondary outcomes included walking speed, bilateral swing time, step length, and maximum toe height, as well as hip, knee, and ankle angle excursions. SWR (p < 0.001) but not SLR (p ≥ 0.05) was increased in all distorted feedback conditions compared to the control condition. Increased swing time on the perturbed side ipsilateral to feedback distortion was observed in the advanced conditions (p < 0.001), while swing time increased bilaterally in the delayed conditions (p < 0.001) but to a larger extent on the unperturbed side contralateral to feedback distortion. Increases in swing time were accompanied by larger maximum toe height as well as larger hip and knee joint excursions (p < 0.05 to p < 0.001). No differences in any outcomes were observed between small and large feedback distortion magnitudes. Distorted footstep sound feedback successfully elicits adaptation in temporal gait symmetry (SWR), with distinct modulation patterns for advanced vs. delayed footstep sounds. Spatial symmetry (SLR) remains unaltered, likely because auditory feedback primarily conveys temporal information. This research lays the groundwork to implement personalized augmented auditory feedback in neurorehabilitation.

Obstacle Detection For Visually Impaired

The paper examines innovative obstacle-detection solutions designed for visually impaired people who do not rely on traditional sensors and recognize the challenges they face when navigating their environment independently. It delves into techniques leveraging alternative sensory modalities such as auditory and tactile feedback, prioritizing user experience and safety. Evaluation criteria encompass effectiveness, ease of use, and affordability, during discussions involve adapting existing infrastructure for tactile navigation and collaboration with guide animal organizations to devise comprehensive solutions. In addition to case studies showing the successful implementation of sensor-free obstacle detection in a wide range of environments, i.e., cities and indoors, challenges related to training and social acceptance of alternative methods will be addressed. In particular, the paper offers beneficial insight into novel approaches to detecting obstacles aimed at improving the mobility and independence of those with visual impairment. Our method uses advanced machine learning algorithms to interpret and predict potential obstacles in real-time. Our system can identify and classify barriers with a high degree of accuracy through analysis of user's sound feedback from their surroundings as well as the use of sophisticated learning techniques. In a wide range of real-world scenarios, we demonstrate the effectiveness of our approach through extensive testing with visually impaired participants. The results show that compared to conventional sensor-based methods, the performance of obstacle detection is significantly improved. In addition, our solution is designed to improve the flexibility, affordability, and ease of integration with existing technologies to create an environment more conducive for people with visual impairment.

Sound Feedback Fuzzy Control for Optimizing Bone Milling Operation During Robot-Assisted Laminectomy

Sound Feedback Fuzzy Control for Optimizing Bone Milling Operation During Robot-Assisted Laminectomy

It Sounds Cool: Exploring Sonification of Mid-Air Haptic Textures Exploration on Texture Judgments, Body Perception, and Motor Behaviour.

Ultrasonic mid-air haptic technology allows for the perceptual rendering of textured surfaces onto the user's hand. Unlike real textured surfaces, however, mid-air haptic feedback lacks implicit multisensory cues needed to reliably infer a texture's attributes (e.g., its roughness). In this article, we combined mid-air haptic textures with congruent sound feedback to investigate how sonification could influence people's 1) explicit judgment of the texture attributes, 2) explicit sensations of their own hand, and 3) implicit motor behavior during haptic exploration. Our results showed that audio cues (presented solely or combined with haptics) influenced participants' judgment of the texture attributes (roughness, hardness, moisture and viscosity), produced some hand sensations (the feeling of having a hand smoother, softer, looser, more flexible, colder, wetter and more natural), and changed participants' speed (moving faster or slower) while exploring the texture. We then conducted a principal component analysis to better understand and visualize the found results and conclude with a short discussion on how audio-haptic associations can be used to create embodied experiences in emerging application scenarios in the metaverse.

Skillful Manipulation of Electronic Musical-Note-Type Instrument Using Industrial Humanoid Robot

Industrial robots contribute significantly to productivity improvements, quality improvements, and cost reductions at production sites. Among the industrial robots, those that can cooperate with humans without safety measures or output limitations on the motors of their axes are known as cooperative robots. In the manufacturing field, there is a growing demand for production lines where humans and robots can coexist and cooperate instead of those where robots perform all processes on their own. In this study, we focus on a cooperative robot fabricated using a 3D resin printer and aim to improve its operation using the same tools as humans. As an example of such an application, we attempt to develop a sound-feedback-based motion for manipulating an electronic musical instrument called an “otamatone”. First, the hardware for grasping the object is created using a 3D printer, and notes on the modeling process are described. We then construct an advanced sound feedback system using the Robot Operating System (ROS) to identify the sounding position and pitch of the instrument. In this study, we propose a partial model-matching method for determining the Proportional–Integral–Derivative (PID) gains of the servomotors of each joint of a robot. Consequently, the accuracy of the robot’s motion improves and the accuracy of the intended musical performance is enhanced.

A Phenomenological Approach to Wearable Technologies and Viscerality: From embodied interaction to biophysical music performance

During the past decade, embodied knowledge has provided novel important insights to rethink mediation technology, thereby paving the way for a transdisciplinary approach to wearable technologies. Stemming from a phenomenological-based approach and considering current trends in sonic interaction design, this article proposes an extensive account on embodied approaches to mediation technology and underlines the increasing importance of somatic knowledge within the field. It also presents an autoethnographic analysis of my own performance, which provides an original contribution to the artistic application of wearable technologies. Stemming from an ongoing research-creation on musical improvisation with biophysical technologies, the case study emphasises how an embodied and visceral approach to interaction can transform wearable devices into an active sensory-perceptual mode of experiencing, which is capable of stimulating the performer’s sensorimotor metaplasticity. The reconfiguration of a body’s automations through the use of sound feedback is a process that unfolds with a high degree of sensitivity in which the body can be poetically understood as an emergent territoriality, inhabited and transfigured by the sound.

Advanced Musical Saw Manipulation by an Industrial Cooperative Humanoid Robot with Passive Sound Feedback

In recent years, collaborative robots able to work together with humans have become widespread in production sites and factory automation fields. In this context, the goal is to provide a production site where cooperative robots can share various types of tools with humans. However, we have not yet reached the point where collaborative robots and humans can share tools for advanced skills. Therefore, it is very important to investigate how a collaborative robot can control advanced tools requiring human skills and the processes for realizing such control. Musical instruments are some of the most difficult tools to handle. It is important to focus on musical instruments because they allow us to evaluate the robot’s manipulation not only by evaluating its movements, but also by evaluating the resultant sound. In this study, we consider a flexible and large deformable musical saw as an unknown and advanced tool difficult for humans to manipulate. In a previous report, a support method for imitating a human was adopted and provided manipulation control based on striking sound feedback using a cooperative humanoid robot. In the present paper, the support method is improved at the tip of the musical saw to realize an advanced wrist motion. In addition, we discuss skillful manipulations based on striking sound feedback control while considering the positions and postures between the collaborative humanoid robot and musical saw.

Clinician acceptability of an antibiotic prescribing knowledge support system for primary care: a mixed-method evaluation of features and context

BackgroundOverprescribing of antibiotics is a major concern as it contributes to antimicrobial resistance. Research has found highly variable antibiotic prescribing in (UK) primary care, and to support more effective stewardship, the BRIT Project (Building Rapid Interventions to optimise prescribing) is implementing an eHealth Knowledge Support System. This will provide unique individualised analytics information to clinicians and patients at the point of care. The objective of the current study was to gauge the acceptability of the system to prescribing healthcare professionals and highlight factors to maximise intervention uptake.MethodsTwo mixed-method co-design workshops were held online with primary care prescribing healthcare professionals (n = 16). Usefulness ratings of example features were collected using online polls and online whiteboards. Verbal discussion and textual comments were analysed thematically using inductive (participant-centred) and deductive perspectives (using the Theoretical Framework of Acceptability).ResultsHierarchical thematic coding generated three overarching themes relevant to intervention use and development. Clinician concerns (focal issues) were safe prescribing, accessible information, autonomy, avoiding duplication, technical issues and time. Requirements were ease and efficiency of use, integration of systems, patient-centeredness, personalisation, and training. Important features of the system included extraction of pertinent information from patient records (such as antibiotic prescribing history), recommended actions, personalised treatment, risk indicators and electronic patient communication leaflets. Anticipated acceptability and intention to use the knowledge support system was moderate to high. Time was identified as a focal cost/ burden, but this would be outweighed if the system improved patient outcomes and increased prescribing confidence.ConclusionClinicians anticipate that an eHealth knowledge support system will be a useful and acceptable way to optimise antibiotic prescribing at the point of care. The mixed method workshop highlighted issues to assist person-centred eHealth intervention development, such as the value of communicating patient outcomes. Important features were identified including the ability to efficiently extract and summarise pertinent information from the patient records, provide explainable and transparent risk information, and personalised information to support patient communication. The Theoretical Framework of Acceptability enabled structured, theoretically sound feedback and creation of a profile to benchmark future evaluations. This may encourage a consistent user-focused approach to guide future eHealth intervention development.

What does competently delivered neuropsychological assessment feedback look like? Development and validation of a competency evaluation tool

Objective: Neuropsychological assessment (NP) feedback helps patients and caregivers understand assessment results to maximise their utility and impact in everyday life. Yet feedback practices are inconsistent and there are no evidence-based guidelines for how feedback should be most effectively delivered. The aim of our study was to develop a psychometrically sound feedback competency checklist, the Psychology Competency Assessment Tool – Feedback (PsyCET-F), for use in research, training, and clinical settings. Method: The Delphi method of expert consensus was used to establish checklist items that clearly described competencies important for NP feedback. To examine the inter-rater reliability of the checklist, two experienced neuropsychologists rated the competencies demonstrated by trainee neuropsychologists across four feedback sessions. Results: After two Delphi rounds, consensus was reached on the 20-item checklist. Consensus was defined as at least 80% agreement amongst the panel of 20 experts. Four item categories resulted from the Delphi: (a) Opening the Session; (b) Applying Specific Feedback Techniques; (c) Engagement, Collaboration, and Alliance; and (d) Structuring and Ending the Session. Inter-rater reliability was moderate (κW = 0.79, p <.001, 80.52% agreement) when using a simple coding system, coded as Beginner, Intermediate, Competent, and Skilful; and strong (κW = 0.82, p <.001) when competency level was coded using an 8-point, detailed coding method. Conclusions: The PsyCET-F is psychometrically sound and fit-for-purpose for measuring competencies in giving NP feedback. It can be used in the training of clinicians to develop effective feedback skills. International benchmarking and usability testing will be conducted in a future study.

Contextual, Radiological Anatomy (RA) Learning needs Evaluation for Curricular Improvement

INTRODUCTION: As a part of the MBBS curriculum review exercise, University of Cyberjaya (UoC), Malaysia had come up with a study to investigate the feedback and learning needs pertaining to radiological anatomy (RA) in pre-clinical teaching. MATERIALS AND METHODS: A single-institutional survey of all five-year medical students was done using an adapted instrument which had both open and close-ended questions on the radiological anatomy teaching received so far and the perception on the teaching methods and content. 405 respondents out of 503 (80%) (year 1=115, year 2= 78, year 3=79, year 4=78, year 5=55) replied. There were totally 136 male and 269 female respondents. RESULTS: Though the overall student learning time (SLT) was adequate, year 3 students (62%) reported inadequate radiological anatomy SLT. Pre[1]clinical students (57.5%) reported more of formal radiological anatomy teaching while clinical students indicated informal teaching (Informal: 15.1 %, Even mix of formal and informal: 56.6 %). Female students reported higher response of adequate SLT (69.1%) and formal teaching (46.9%) compared to males. Small group learning such as gross anatomy practical sessions, problem-based learning, clinical skills teaching, and clinical correlates sessions were recommended. Abdomen and thorax were the most preferred regions where radiological anatomy could be explored further. X-ray followed by CT and MRI were the most favoured radiological modalities to learn topographical anatomy. CONCLUSION: The study provided sound feedback on the existing radiological anatomy teaching practices. Data shows stark contrast between the needs of the students and the current practices indicating that it is quite substantial for curriculum review.

Audio Feedback with the Use of a Smartphone in Sailing Training among Windsurfers

The open-water training conditions in sailing sports limit the coach’s ability to provide instructions. Auditory feedback provided using a smartphone application in real-time seems to be a promising tool in the training process. The aim of the study was to assess the usefulness of a smartphone application created to support tactical decisions via an auditory display. Thirteen successful windsurfers competing in RS:X class took part in the study. The results, collected with the use of a questionnaire, related to the technical and aesthetic aspects of the functions as well as decision-making assistance of the application during upwind sailing races. Most of the competitors positively evaluated application function (54–85%). Real-time information about the deviation from the set course and information about potential tack change due to a changed wind direction were statistically significantly more helpful for less experienced windsurfers (rho = −0.68 and rho = −0.78, respectively) and those with lower sports level (rho = −0.63 and rho = −0.65, respectively). It can be concluded that the use of sound feedback in the conditions of training on-water in sailing has potential, primarily for younger and less experienced competitors. Quantitative evaluations of the sailing performance should be considered in further research on the functionality of the application.

Agricultural Machinery Operator Monitoring System (Ag-OMS): A Machine Learning Approach for Real-Time Operator Safety Assessment

Highlights A machine learning-based real-time monitoring system for agricultural machinery operators was developed. Categorization of tractor operators’ behaviors in real-time into low, medium, and high-risk safety behaviors. Visual and sound feedback alert system of Ag-OMS triggered when operators engaged in unsafe operating behaviors. ABSTRACT. The 2015 CS-CASH (Central States Center for Agricultural Safety and Health, 2015) Injury Surveillance Surveys showed that around 19% of injuries to agricultural producers are related to tractors or large agricultural machinery, yet only a limited number of studies are found that address tools and methods for monitoring safety behaviors of agricultural machinery operators in real-time. The current safety behavior monitoring approaches require an in-person presence, which can be both time- and cost-inefficient, and the other available methods lack a feedback element to alert operators in real-time. As a result, the research presented in this study aimed to develop an automated approach to monitoring tractor operators' safety behaviors through the use of a trained machine learning (ML) model and a feedback system to alert operators when they engage in unsafe practices. For the ML model development, a skeleton-detecting algorithm called OpenPose was used to detect real-time human postures in a livestreaming video feed from a camera installed in the tractor cab. The model was then trained on three separate categories of tractor operators’ safety operating behaviors, and this trained classifier was used to label operators’ safety behaviors in real time based on the three safety classes. A feedback mechanism controlled by an onboard microcontroller was then used to alert the operators when unsafe operating behavior was detected to facilitate safe practices. This monitoring system, named Ag-OMS (Agricultural Machinery Operators Monitoring System), monitored the ingress/egress operators’ behaviors in real-time entering and exiting the tractor cab. The Ag-OMS successfully identified the ingress/egress operators’ behaviors with an accuracy of 97% on the testing datasets for all safety risk categories. Keywords: Ag-OMS, Machine learning (ML), Safety behaviors, OpenPose, Tractor operator.

Research on the Design Method of Pure Electric Vehicle Acceleration Motion Sense Sound Simulation System

Due to the emerging trend of energy conservation and emission reduction around the world, the new energy vehicle industry has achieved rapid development. However, there are new challenges regarding vehicle NVH(noise, vibration, and harshness). When a pure electric vehicle is being driven, the inside of the vehicle is relatively quiet, which cannot bring the driver sound feedback reflecting the change of the vehicle state. In order to solve this problem, this paper studies the design method of a sound simulation system for acceleration motion in pure electric vehicles. In this paper, the motion characteristics of automobile engine acceleration sound, sound signal analysis and processing, subjective evaluation of sound quality, and sound synthesis strategy are studied. By reading the vehicle running state data on the CAN bus of pure electric vehicles, the goal of engine motion sense sound simulation during vehicle acceleration is achieved. This helps to enhance driving feedback and improve user driving experience.

Study on Musical Saw Bowing Motion with an Industrial Cooperative Humanoid Robot

The objective of this study was to automate the dual-arm coordination of an industrial humanoid robot when using a musical saw as a percussion instrument to produce a target sound. Especially, this report focuses on a humanoid robot with a characteristic of the real-time control to replace the traditional teaching and playback motion control. Meanwhile, it is assumed that the humanoid robot works in the environment that is near to a human being. To adapt in such situation, we aim to achieve the complex work using an advanced tool with its robot, as we perform a skillful motion. In the present report, we examine the performance of a musical saw using a bow because it is a kind of complex work using an unknown and advanced tool. Moreover, both the control method of the arm of the robot and the performance of the bow are discussed to construct a sound feedback control approach. As a result, it is demonstrated that the proposed approach has potential for both industrial and recreational applications of humanoid robots in human occupied environments.

Sound Feedback for Social Distance: The Case for Public Interventions during a Pandemic

Within the field of movement sensing and sound interaction research, multi-user systems have gradually gained interest as a means to facilitate an expressive non-verbal dialogue. When tied with studies grounded in psychology and choreographic theory, we consider the qualities of interaction that foster an elevated sense of social connectedness, non-contingent to occupying one’s personal space. Upon reflection of the newly adopted social distancing concept, we orchestrate a technological intervention, starting with interpersonal distance and sound at the core of interaction. Materialised as a set of sensory face-masks, a novel wearable system was developed and tested in the context of a live public performance from which we obtain the user’s individual perspectives and correlate this with patterns identified in the recorded data. We identify and discuss traits of the user’s behaviour that were accredited to the system’s influence and construct four fundamental design considerations for physically distanced sound interaction. The study concludes with essential technical reflections, accompanied by an adaptation for a pervasive sensory intervention that is finally deployed in an open public space.

SoundWatch

Smartwatches have the potential to provide glanceable, always-available sound feedback to people who are deaf or hard of hearing (DHH). We present SoundWatch, a smartwatch-based deep learning application to sense, classify, and provide feedback about sounds occurring in the environment. To design SoundWatch, we first examined four low-resource sound classification models across four device architectures: watch-only, watch+phone, watch+phone+cloud, and watch+cloud. We found that the best model, VGG-lite, performed similar to the state of the art for nonportable devices although requiring substantially less memory (∼1/3 rd ) and that the watch+phone architecture provided the best balance among CPU, memory, network usage, and latency. Based on these results, we built and conducted a lab evaluation of our smartwatch app with eight DHH participants. We found support for our sound classification app but also uncovered concerns with misclassifications, latency, and privacy.

Utilizing a Learning Management System to Provide Nursing Professional Development.

The provider unit involved in this project was based in a university setting within a school of nursing and serves both the university nursing faculty and nurses within the community. To support effective online content design principles, usability, a connection to the content, and a method for participants to provide sound feedback, a nurse planner for the unit and an instructional designer in the university collaborated to transition nursing professional development activities to an online format utilizing a learning management system. Virtual learning is viable and a potentially effective option to provide interactive and innovative professional development.

Ankle-Worn Sensor Sleeve to increase walking motivation

In this study, we propose the Ankle-Worn Sensor Sleeve to help people maintain their health. Furthermore, our approach uses this sensor sleeve to improve walking motivation by making the walking motion more sensible. In this research, we pursue the design of a wearable device that users can wear as a “shoe accessory,” with the aim of promoting people’s walking motivation. This device is ankle-worn and generates electricity using the physical flexion and extension of the ankle, detects and acquires the amount of electricity generated, and uses the resulting power to produce sound and light feedback while walking. The Sleeve is designed to support health problems, such as locomotive syndrome and dementia, which are caused by physical inactivity. This article presents the results of a questionnaire survey conducted on 172 people who experienced or observed the device during exhibitions. The results reveal that this device increased people’s interest and motivation to walk, including those who did not like to walk.

Fostering Social Interaction Through Sound Feedback: Sentire

Sentire is a body–machine interface that sonifies motor behaviour in real time and a participatory, interactive performance in which two people use their physical movements to collaboratively create sound while constantly being influenced by the results. Based on our informal observation that basal social behaviours emerge during Sentire performances, the present article investigates our principal hypothesis that Sentire can foster basic mechanisms underlying non-verbal social interaction. We illustrate how coordination serves as a crucial basic mechanism for social interaction, and consider how it is addressed by various therapeutic approaches, including therapeutic use of real-time auditory feedback. Then we argue that the implementation of Sentire may be fruitful in healthcare contexts and in promoting general well-being. We describe how the Sentire system has been developed further within the scope of the research project ‘Social interaction through sound feedback–Sentire’ that combines human–computer interaction, sound design and real-world research, against the background of the relationship between sound, sociality and therapy. The question concerning how interaction is facilitated through Sentire is addressed through the first results of behavioural analysis using structured observation, which allows for a quasi-quantitative sequential analysis of interactive behaviour.

A Noise Control Method Using Adaptive Adjustable Parametric Array Loudspeaker to Eliminate Environmental Noise in Real Time.

Long-term exposure to environmental noise is dangerous to human health. Therefore, there is an urgent need to suppress or eliminate environmental noise. Due to the limitation of environmental space, the use of reverse sound waves emitted by loudspeakers for noise elimination has been widely used in noise control. However, because of the omni-directionality of sound propagation, a traditional voice coil loudspeaker (VCL) is used as a secondary source (emission reverse sound wave). It is easy to increase the sound pressure in non-target areas and form significant acoustic feedback to the reference source. Therefore, we propose an online secondary path modeling method using an adjustable parametric array loudspeaker (PAL) based on ultrasounds to eliminate environmental noise in real time. According to the different distance of the target, the size of the PAL is adjusted adaptively to realize the noise control of different long-distance targets. The distribution of quiet areas is discussed. The experimental results showed that a PAL as a secondary source had the same noise reduction effect as a traditional VCL, but it had longer propagation distance, smaller sound feedback and a more regular and controllable distribution of quiet areas. These research findings have great potential for improving environmental noise and creating a quiet environment.