Voice Activated IoT Devices for Healthcare: Design Challenges and Emerging Applications

Spachos, Petros; Gregori, Stefano; Deen, M. Jamal

doi:10.1109/tcsii.2022.3179680

Cited by 14 publications

(8 citation statements)

References 74 publications

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“…A large amount of personal data is collected, resulting in security and privacy concerns due to the nature of the data used for analysis [3]. The wearable devices' limitations on processing capabilities lead to vulnerabilities and potential leakages in sensitive patient information [4]. Another issue is the integrity and reliability of the service [5].…”

Section: Introductionmentioning

confidence: 99%

Federated Learning and Blockchain-Enabled Fog-IoT Platform for Wearables in Predictive Healthcare

Baucas

Spachos

Plataniotis

2023

IEEE Trans. Comput. Soc. Syst.

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Over the years, the popularity and usage of wearable Internet of Things (IoT) devices in several healthcare services are increased. Among the services that benefit from the usage of such devices is predictive analysis, which can improve early diagnosis in e-health. However, due to the limitations of wearable IoT devices, challenges in data privacy, service integrity, and network structure adaptability arose. To address these concerns, we propose a platform using federated learning and private blockchain technology within a fog-IoT network. These technologies have privacy-preserving features securing data within the network. We utilized the fog-IoT network's distributive structure to create an adaptive network for wearable IoT devices. We designed a testbed to examine the proposed platform's ability to preserve the integrity of a classifier. According to experimental results, the introduced implementation can effectively preserve a patient's privacy and a predictive service's integrity. We further investigated the contributions of other technologies to the security and adaptability of the IoT network. Overall, we proved the feasibility of our platform in addressing significant security and privacy challenges of wearable IoT devices in predictive healthcare through analysis, simulation, and experimentation.

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Section: Introductionmentioning

confidence: 99%

Federated Learning and Blockchain-Enabled Fog-IoT Platform for Wearables in Predictive Healthcare

Baucas

Spachos

Plataniotis

2023

IEEE Trans. Comput. Soc. Syst.

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“…These effects have stimulated the exploration of new sustainable and clean energy resources. The increasingly rapid-pace advances in internet-of-things (IoT) 1 , 2 and the ubiquitous use of smart sensors and devices 3 , 4 require new techniques to power them. Solar energy is considered one of the abundant and clean resources on earth.…”

Section: Introductionmentioning

confidence: 99%

Optimized polarization-independent Chand-Bali nano-antenna for thermal IR energy harvesting

Elsharabasy,

Bakr,

Deen

2023

Sci Rep

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A novel, polarization-independent, wide-angle reception Chand-Bali nano-antenna is proposed. An adjoint-based optimization algorithm is used to create the same resonance at both linear polarizations of the incident radiation. The nano-antenna optimal parameters reveal that two hot spots with a strong field enhancement are created. These hot-spots could be integrated with metal–insulator–metal (MIM) diodes to form a rectenna for infrared (IR) energy harvesting. The metallic resonators allow for selecting several materials to facilitate the fabrication of the nano-antenna and the MIM diode. The Chand-Bali-based IR rectennas are investigated and simulations demonstrate an improvement of more than one order of magnitude in efficiency compared to ones using traditional nano-antennas.

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“…None of the existing VAD overview papers [27]- [31] focus on comparing and benchmarking the hardware implementations; instead they focus on different classification techniques [27], [28] or algorithms [29]- [31]. An overview on the design challenges faced by voice-activated IoT devices for the healthcare industry is presented in [32]. This overview addresses the high level requirements and challenges for a VAD in the medical field, but does not provide details about the implementation of such systems.…”

mentioning

confidence: 99%

Hardware Implementations for Voice Activity Detection: Trends, Challenges and Outlook

Yadav

Legaspi

Alink

et al. 2023

IEEE Trans. Circuits Syst. I

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Voice Activity Detection (VAD) is a technique used to identify the presence of human voice in an audio signal. It is implemented as an always-on component in most speech processing applications. As speech is absent most of the time, this component typically dominates the overall average power consumption of the system (excluding microphone). The widespread usage in speech applications and the need for ultra low power VAD have led to a plethora of algorithms and implementations in the hardware domain, necessitating a comprehensive study and analysis to understand (real-time) requirements, different design parameters, testing strategies, but also to identify design trends, challenges and guidelines for future implementations and testing of VAD devices. A scoping review was conducted to identify the articles for hardware implementations of VAD from January 2010 -December 2021, the results of which are presented in this article. The results highlight a big design space being used for VAD along with a lack of standard testing methodology and usage of application-dependent performance metrics. An increased usage of filter-based feature extractors along with neural-networkbased classifiers is observed. Due to lack of standardisation, no other trends can be established from the results. A set of rules and guidelines are therefore provided to facilitate the future development and benchmarking of VADs.

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Voice Activated IoT Devices for Healthcare: Design Challenges and Emerging Applications

Cited by 14 publications

References 74 publications

Federated Learning and Blockchain-Enabled Fog-IoT Platform for Wearables in Predictive Healthcare

Federated Learning and Blockchain-Enabled Fog-IoT Platform for Wearables in Predictive Healthcare

Optimized polarization-independent Chand-Bali nano-antenna for thermal IR energy harvesting

Hardware Implementations for Voice Activity Detection: Trends, Challenges and Outlook

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