Hearing aid devices for smart cities: A survey

Garcia-Espinosa, Eduardo; Longoria-Gándara, O.; Veloz-Guerrero, A.; Riva, Guillermo

doi:10.1109/isc2.2015.7366198

Cited by 7 publications

(4 citation statements)

References 9 publications

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“…Smart hearing technology can enhance spatial sense or help in focusing on the sound coming from a specific direction (Ricketts, 2001). Furthermore, realworld sounds can be augmented by virtual sound elements, creating a hybrid sound experience and a personalized sound environment (Härmä et al, 2004;Garcia-Espinosa et al, 2015). Due to the closeness of the blood vessels in the ear, the earpiece could incorporate additional sensors to measure physiological signals.…”

Section: Augmented Sensesmentioning

confidence: 99%

Human augmentation: Past, present and future

Raisamo

Rakkolainen

Majaranta

et al. 2019

International Journal of Human-Computer Studies

155

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Human augmentation is a field of research that aims to enhance human abilities through medicine or technology. This has historically been achieved by consuming chemical substances that improve a selected ability or by installing implants which require medical operations. Both of these methods of augmentation can be invasive. Augmented abilities have also been achieved with external tools, such as eyeglasses, binoculars, microscopes or highly sensitive microphones. Lately, augmented reality and multimodal interaction technologies have enabled non-invasive ways to augment human.In this article, we first discuss the field and related terms. We provide relevant definitions based on the present understanding of the field. This is followed by a summary of existing work in augmented senses, action, and cognition. Our contribution to the future includes a model for wearable augmentation. In addition, we present a call for research to realize this vision. Then, we discuss future human abilities. Wearable technologies may act as mediators for human augmentation, in the same manner as eyeglasses once revolutionized human vision. Non-invasive and easy-to-use wearable extensions will enable lengthening the active life for aging citizens or supporting the full inclusion of people with special needs in society, but there are also potential problems. Therefore, we conclude by discussing ethical and societal issues: privacy, social manipulation, autonomy and side effects, accessibility, safety and balance, and unpredictable future.

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Section: Augmented Sensesmentioning

confidence: 99%

Human augmentation: Past, present and future

Raisamo

Rakkolainen

Majaranta

et al. 2019

International Journal of Human-Computer Studies

155

View full text Add to dashboard Cite

show abstract

“…The advancement in digital signal processing has improved the performance of hearing aids and Bluetooth low energy protocol, enabling it to answer phone calls, provide voice assistance, listen to music, launch apps on smartphones, etc. A hearing aid can be intelligently used for audio noise cancellation, creating personal sound zones, specific audio broadcast, public audio alerts, and customized sound streaming for objects using Bluetooth low-energy-enabled hearing devices as presented in [52].…”

Section: Taxonomy On Smart Healthcare Technologiesmentioning

confidence: 99%

A Taxonomy on Smart Healthcare Technologies: Security Framework, Case Study, and Future Directions

et al. 2022

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There is a massive transformation in the traditional healthcare system from the specialist-centric approach to the patient-centric approach by adopting modern and intelligent healthcare solutions to build a smart healthcare system. It permits patients to directly share their medical data with the specialist for remote diagnosis without any human intervention. Furthermore, the remote monitoring of patients utilizing wearable sensors, Internet of Things (IoT) technologies, and artificial intelligence (AI) has made the treatment readily accessible and affordable. However, the advancement also brings several security and privacy concerns that poorly maneuvered the effective performance of the smart healthcare system. An attacker can exploit the IoT infrastructure, perform an adversarial attack on AI models, and proliferate resource starvation attacks in smart healthcare system. To overcome the aforementioned issues, in this survey, we extensively reviewed and created a comprehensive taxonomy of various smart healthcare technologies such as wearable devices, digital healthcare, and body area networks (BANs), along with their security aspects and solutions for the smart healthcare system. Moreover, we propose an AI-based architecture with the 6G network interface to secure the data exchange between patients and medical practitioners. We have examined our proposed architecture with the case study based on the COVID-19 pandemic by adopting unmanned aerial vehicles (UAVs) for data exchange. The performance of the proposed architecture is evaluated using various machine learning (ML) classification algorithms such as random forest (RF), naive Bayes (NB), logistic regression (LR), linear discriminant analysis (LDA), and perceptron. The RF classification algorithm outperforms the conventional algorithms in terms of accuracy, i.e., 98%. Finally, we present open issues and research challenges associated with smart healthcare technologies.

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“…There are many reasons for the low adoption rate of HA, including echo, short standby time, and lack of aesthetic appeal. However, the main reasons are high cost and poor user experience [7]- [10].…”

Section: Introductionmentioning

confidence: 99%

A Smart Binaural Hearing Aid Architecture Leveraging a Smartphone APP With Deep-Learning Speech Enhancement

Chen

Sun

et al. 2020

IEEE Access

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This paper presents a smartphone-based binaural hearing aid architecture for improving the speech intelligibility of hearing aid users. The proposed system consists of an earpiece, a smartphone and an application that performs real-time speech enhancement. The speaker's voice, which is picked up by the microphone of the earpiece that is worn on the ear, is transmitted to the smartphone via wireless technology. After the speech intelligibility is improved in real time by the deep learning speech enhancement application, it is returned to the earpiece and generates sound. Deep learning speech enhancement algorithms can be used without performing burdensome calculations on the processors in the hearing aid. The results showed that the average usage of the central processing unit in the smartphone was approximately 26%, and the signal-tonoise ratios improve by at least 20%. The presented objective and subjective results show that the proposed method achieves comparatively more noise suppression without distorting the audio. INDEX TERMS Binaural hearing aids, smartphone, real-time se app, e-health, deep learning.

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Hearing aid devices for smart cities: A survey

Cited by 7 publications

References 9 publications

Human augmentation: Past, present and future

Human augmentation: Past, present and future

A Taxonomy on Smart Healthcare Technologies: Security Framework, Case Study, and Future Directions

A Smart Binaural Hearing Aid Architecture Leveraging a Smartphone APP With Deep-Learning Speech Enhancement

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