Predicting unreliable response patterns in smartphone health surveys: A case study with the mood survey

Vhaduri, Sudip; Cho, Jaea; Meng, Kexin

doi:10.1016/j.smhl.2023.100398

Cited by 2 publications

(1 citation statement)

References 64 publications

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“…While our findings in this work show the promise of developing models to detect cough symptoms utilizing a user's background environment knowledge about the presence of different types of sounds, the effective applicability of such models for disease diagnosis depends on many other factors, including detecting other symptoms (e.g., breathing difficulty) and integration of the self-reported subjective symptoms in addition to objective predictions [69], [70], [71], [72], [73], [74], [75]. Additionally, people's medical history and health records can be integrated for better diagnosis of diseases and people's conditions.…”

Section: Discussionmentioning

confidence: 96%

Environment Knowledge-Driven Generic Models to Detect Coughs From Audio Recordings

Vhaduri

Dibbo

Kim

2023

IEEE Open J. Eng. Med. Biol.

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Goal: Millions of people are dying due to respiratory diseases, such as COVID-19 and asthma, which are often characterized by some common symptoms, including coughing. Therefore, objective reporting of cough symptoms utilizing environment-adaptive machine-learning models with microphone sensing can directly contribute to respiratory disease diagnosis and patient care. Methods: In this work, we present three generic modeling approaches – unguided , semi-guided , and guided approaches considering three potential scenarios, i.e., when a user has no prior knowledge, some knowledge, and detailed knowledge about the environments, respectively. Results: From detailed analysis with three datasets, we find that guided models are up to 28% more accurate than the unguided models. We find reasonable performance when assessing the applicability of our models using three additional datasets, including two open-sourced cough datasets. Conclusions: Though guided models outperform other models, they require a better understanding of the environment.

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Section: Discussionmentioning

confidence: 96%

Environment Knowledge-Driven Generic Models to Detect Coughs From Audio Recordings

Vhaduri

Dibbo

Kim

2023

IEEE Open J. Eng. Med. Biol.

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Challenges and Opportunities of Biometric User Authentication in the Age of IoT: A Survey

Lien¹,

Vhaduri

2023

ACM Comput. Surv.

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While the Internet of Things (IoT) devices, such as smartwatches, provide a range of services from managing financial transactions to monitoring smart homes, these devices often lead to gateways for malicious access to a user’s cyber-physical space. Biometric-based authentications are becoming popular to secure IoT devices and provide other services. However, when to use what type of biometrics remains challenging due to various factors, including sensing and computing requirements, user interaction requirements, stability over time, and application scenarios, among others. Unlike soft biometrics, e.g., gait, traditional biometrics, e.g., iris, are more stable over time but require active user input and robust sensing and computing, which limits their continuous adaptability to secure a user’s cyber-physical space. Additionally, the integration of new sensors to IoT devices brings opportunistic data types that can individually or in combination with other common biometrics to identify a user. There is a dearth of knowledge about the limitations and applications of new opportunistic biometrics and their combinations with existing biometrics obtained from single or multiple IoT-connected devices. Therefore, this manuscript thoroughly discusses different biometrics that can be implemented on IoT devices to understand the potential of biometric authentications better.

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Predicting unreliable response patterns in smartphone health surveys: A case study with the mood survey

Cited by 2 publications

References 64 publications

Environment Knowledge-Driven Generic Models to Detect Coughs From Audio Recordings

Environment Knowledge-Driven Generic Models to Detect Coughs From Audio Recordings

Challenges and Opportunities of Biometric User Authentication in the Age of IoT: A Survey

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