Poster: Human Presence Detection After Earthquakes: An AI-Based Implicit User Interface on the Smartphone DOI
Enrico Bassetti,

Gianmarco Cavallaccio,

Maria De Marsico

et al.

Published: Sept. 14, 2023

One of the main challenges rescue operations after a devastating earthquake is timely location people trapped under debris. We propose system that exploits smartphone to detect presence and implicitly interact with person in buildings. It leverages phone microphone sound waves generated by human breathing, heartbeat, movement. analyzes signals on itself using deep learning. A server collecting results can support search-and-rescue or trigger further actions, such as an emergency call. The preliminary evaluation based proof-of-concept Android app demonstrate accurate detection within specific range smartphone.

Language: Английский

Automated detection and forecasting of COVID-19 using deep learning techniques: A review DOI
Afshin Shoeibi, Marjane Khodatars, Mahboobeh Jafari

et al.

Neurocomputing, Journal Year: 2024, Volume and Issue: 577, P. 127317 - 127317

Published: Jan. 26, 2024

Language: Английский

Citations

53
Coswara: A respiratory sounds and symptoms dataset for remote screening of SARS-CoV-2 infection DOI Creative Commons
Debarpan Bhattacharya, Neeraj Sharma, Debottam Dutta

et al.

Scientific Data, Journal Year: 2023, Volume and Issue: 10(1)

Published: June 22, 2023

Abstract This paper presents the Coswara dataset, a dataset containing diverse set of respiratory sounds and rich meta-data, recorded between April-2020 February-2022 from 2635 individuals (1819 SARS-CoV-2 negative, 674 positive, 142 recovered subjects). The contained nine sound categories associated with variants breathing, cough speech. metadata demographic information age, gender geographic location, as well health relating to symptoms, pre-existing ailments, comorbidity test status. Our study is first its kind manually annotate audio quality entire (amounting 65 hours) through manual listening. summarizes data collection procedure, demographic, symptoms information. A COVID-19 classifier based on bi-directional long short-term (BLSTM) architecture, trained evaluated different population sub-groups in understand bias/fairness model. enabled analysis impact gender, date recording, language proficiency detection performance.

Language: Английский

Citations

31
The voice of COVID-19: Breath and cough recording classification with temporal decision trees and random forests DOI Open Access

F. Manzella,

Giovanni Pagliarini, Guido Sciavicco

et al.

Artificial Intelligence in Medicine, Journal Year: 2023, Volume and Issue: 137, P. 102486 - 102486

Published: Feb. 4, 2023

Language: Английский

Citations

26
Mobile Apps for COVID-19 Detection and Diagnosis for Future Pandemic Control: Multidimensional Systematic Review DOI Creative Commons
Mehdi Gheisari, Mustafa Ghaderzadeh, Huxiong Li

et al.

JMIR mhealth and uhealth, Journal Year: 2023, Volume and Issue: 12, P. e44406 - e44406

Published: Aug. 18, 2023

In the modern world, mobile apps are essential for human advancement, and pandemic control is no exception. The use of technology detection diagnosis COVID-19 has been subject numerous investigations, although thorough analysis prevention conducted using apps, creating a gap.

Language: Английский

Citations

22
Respiratory Diseases Diagnosis Using Audio Analysis and Artificial Intelligence: A Systematic Review DOI Creative Commons

Panagiotis Kapetanidis,

Fotios Kalioras,

Constantinos Tsakonas

et al.

Sensors, Journal Year: 2024, Volume and Issue: 24(4), P. 1173 - 1173

Published: Feb. 10, 2024

Respiratory diseases represent a significant global burden, necessitating efficient diagnostic methods for timely intervention. Digital biomarkers based on audio, acoustics, and sound from the upper lower respiratory system, as well voice, have emerged valuable indicators of functionality. Recent advancements in machine learning (ML) algorithms offer promising avenues identification diagnosis through analysis processing such audio-based biomarkers. An ever-increasing number studies employ ML techniques to extract meaningful information audio Beyond disease identification, these explore diverse aspects recognition cough sounds amidst environmental noise, detect symptoms like wheezes crackles, voice/speech evaluation human voice abnormalities. To provide more in-depth analysis, this review examines 75 relevant across three distinct areas concern diseases’ symptoms: (a) detection, (b) (c) diagnostics speech. Furthermore, publicly available datasets commonly utilized domain are presented. It is observed that research trends influenced by pandemic, with surge COVID-19 diagnosis, mobile data acquisition, remote systems.

Language: Английский

Citations

7
A novel deep learning model to detect COVID-19 based on wavelet features extracted from Mel-scale spectrogram of patients’ cough and breathing sounds DOI Creative Commons
Mohammed Aly, Nouf Saeed Alotaibi

Informatics in Medicine Unlocked, Journal Year: 2022, Volume and Issue: 32, P. 101049 - 101049

Published: Jan. 1, 2022

The goal of this paper is to classify the various cough and breath sounds COVID-19 artefacts in signals from dynamic real-life environments. main reason for choosing than other common symptoms detect patients comfort their homes, so that they do not overload Medicare system therefore unwittingly spread disease by regularly monitoring themselves. presented model includes two phases. first phase sound-to-image transformation, which improved Mel-scale spectrogram approach. second consists extraction features classification using nine deep transfer models (ResNet18/34/50/100/101, GoogLeNet, SqueezeNet, MobileNetv2, NasNetmobile). dataset contains information data almost 1600 people (1185 Male 415 Female) all over world. Our most accurate, its accuracy 99.2% according SGDM optimizer. good enough a large set labelled may be used check possibility generalization. results demonstrate ResNet18 best stable classifying tones restricted dataset, with sensitivity 98.3% specificity 97.8%. Finally, shown more trustworthy accurate any present model. Cough study promising put extrapolation generalization test.

Language: Английский

Citations

23
The use of artificial intelligence for delivery of essential health services across WHO regions: a scoping review DOI Creative Commons
Joseph Okeibunor, Anelisa Jaca, Chinwe Juliana Iwu

et al.

Frontiers in Public Health, Journal Year: 2023, Volume and Issue: 11

Published: July 4, 2023

Background Artificial intelligence (AI) is a broad outlet of computer science aimed at constructing machines capable simulating and performing tasks usually done by human beings. The aim this scoping review to map existing evidence on the use AI in delivery medical care. Methods We searched PubMed Scopus March 2022, screened identified records for eligibility, assessed full texts potentially eligible publications, extracted data from included studies duplicate, resolving differences through discussion, arbitration, consensus. then conducted narrative synthesis data. Results Several methods have been used detect, diagnose, classify, manage, treat, monitor prognosis various health issues. These models conditions, including communicable diseases, non-communicable mental health. Conclusions Presently available shows that models, predominantly deep learning, machine can significantly advance care regarding detection, diagnosis, management, monitoring different illnesses.

Language: Английский

Citations

15
Smartphone-based point-of-care testing of the SARS-CoV-2: A systematic review DOI Creative Commons

Berlanty A. Zayed,

Ahmed N. Ali,

Alaa A. Elgebaly

et al.

Scientific African, Journal Year: 2023, Volume and Issue: 21, P. e01757 - e01757

Published: June 10, 2023

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus's worldwide pandemic has highlighted the urgent need for reliable, quick, and affordable diagnostic tests comprehending controlling epidemic by tracking world population. Given how crucial it is to monitor manage pandemic, researchers have recently concentrated on creating quick detection techniques. Although PCR still preferred clinical test, there a pressing substitutes that are sufficiently rapid cost-effective provide diagnosis at time of use. creation simple POC equipment necessary home testing. Our review's goal an overview many methods utilized identify SARS-CoV in various samples utilizing portable devices, as well any potential applications smartphones epidemiological research detection. point care (POC) employs range microfluidic biosensors based smartphones, including molecular sensors, immunological biosensors, hybrid imaging biosensors. For example, number tools been created COVID-19, theories. Integrated devices can be using loop-mediated isothermal amplification, which combines amplification with colorimetric Electrochemical approaches regarded substitute optical sensing techniques utilize fluorescence being more beneficial Minimizing simplicity used detection, together amplify DNA or RNA under constant temperature conditions, without repeated heating cooling cycles. Many virus data visualization, making these user-friendly broadly distributed throughout nations. Overall, our provides review different novel, non-invasive, affordable, efficient identifying COVID-19 contagious infected people halting disease's transmission.

Language: Английский

Citations

11
Voice EHR: introducing multimodal audio data for health DOI Creative Commons

James Anibal,

Hannah Huth, Ming Li

et al.

Frontiers in Digital Health, Journal Year: 2025, Volume and Issue: 6

Published: Jan. 28, 2025

Introduction Artificial intelligence (AI) models trained on audio data may have the potential to rapidly perform clinical tasks, enhancing medical decision-making and potentially improving outcomes through early detection. Existing technologies depend limited datasets collected with expensive recording equipment in high-income countries, which challenges deployment resource-constrained, high-volume settings where a profound impact health equity. Methods This report introduces novel protocol for collection corresponding application that captures information guided questions. Results To demonstrate of Voice EHR as biomarker health, initial experiments quality multiple case studies are presented this report. Large language (LLMs) were used compare transcribed (from same patients) conventional techniques like choice Information contained samples was consistently rated equally or more relevant evaluation. Discussion The HEAR facilitates an electronic record (“Voice EHR”) contain complex biomarkers from voice/respiratory features, speech patterns, spoken semantic meaning longitudinal context–potentially compensating typical limitations unimodal datasets.

Language: Английский

Citations

0
COVID-19 Detection from Optimized Features of Breathing Audio Signals Using Explainable Ensemble Machine Learning DOI Creative Commons
Shahnaz Sultana, A. B. M. Aowlad Hossain, Jahangir Alam

et al.

Results in Control and Optimization, Journal Year: 2025, Volume and Issue: unknown, P. 100538 - 100538

Published: Feb. 1, 2025

Language: Английский

Citations

0