Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 9 de 9
Filter
1.
2022 IEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2161374

ABSTRACT

Coughing is a common symptom across different clinical conditions and has gained further relevance in the past years due to the COVID-19 pandemic. An automated cough detection for continuous health monitoring could be developed using Earbud, a wearable sensor platform with audio and inertial measurement unit (IMU) sensors. Though several previous works have investigated audio-based automated cough detection, audio-based methods can be highly power-consuming for wearable sensor applications and raise privacy concerns. In this work, we develop IMU-based cough detection using a template matching-based algorithm. IMU provides a low-power privacy-preserving solution to complement audio-based algorithms. Similarly, template matching has low computational and memory needs, suitable for on-device implementations. The proposed method uses feature transformation of IMU signal and unsupervised representative template selection to improve upon our previous work. We obtained an AUC (AUC-ROC) of 0.85 and 0.83 for cough detection in a lab-based dataset with 45 participants and a controlled free-living dataset with 15 participants, respectively. These represent an AUC improvement of 0.08 and 0.10 compared to the previous work. Additionally, we conducted an uncontrolled free-living study with 7 participants where continuous measurements over a week were obtained from each participant. Our cough detection method achieved an AUC of 0.85 in the study, indicating that the proposed IMU-based cough detection translates well to the varied challenging scenarios present in free-living conditions. © 2022 IEEE.

2.
Nephro-Urology Monthly ; 14(3), 2022.
Article in English | EMBASE | ID: covidwho-2044160

ABSTRACT

Background: Despite all of the research on the risk factors for severe COVID-19, there are still many unknowns about the course of COVID-19 in various populations. Inevitable exposure of dialysis patients, one of the more vulnerable groups for infectious diseases, to COVID-19 concerns many researchers. Furthermore, studies on the mortality rate and risk factors regarding dialysis patients are somewhat inconsistent. Also, it has been suggested that factors such as ethnicity can contribute to that matter. Objectives: We aimed to evaluate the mortality rate of dialysis patients who contracted COVID-19 in the Iranian population. Methods: In this cross-sectional study, we presented the experiences of 4 dialysis centers with a total of 309 dialysis patients (Tehran, Iran) during the COVID-19 pandemic to assess the mortality rate and associated risk factors. Results: Among 309 dialysis patients, 58 patients contracted the disease, and the total mortality rate in this study was 41%. It was observed that although the guidelines for screening patients were similar in these 4 centers, the centers with regular COVID-19 screening for staff members had much lower mortality and infection rate. The most common symptoms in patients were fever, dry cough, and chills. Furthermore, comorbidities such as diabetes can also increase the risk of mortality. Conclusions: This study, along with other studies, can be utilized in developing guidelines for dialysis centers in the COVID-19 pandemic and future pandemics.

3.
47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 ; 2022-May:1-5, 2022.
Article in English | Scopus | ID: covidwho-1891392

ABSTRACT

Persistent coughs are a major symptom of respiratory-related diseases. Increasing research attention has been paid to detecting coughs using wearables, especially during the COVID-19 pandemic. Microphone is most widely used sensor to detect coughs. However, the intense power consumption needed to process audio hinders continuous audio-based cough detection on battery-limited commercial wearables, such as earbuds. We present CoughTrigger, which utilizes a lower-power sensor, inertial measurement unit (IMU), in earbuds as a cough detection activator to trigger a higher-power sensor for audio processing and classification. It runs all-the-time as a standby service with minimal battery consumption and triggers the audio-based cough detection when a candidate cough is detected from IMU. Besides, the use of IMU brings the benefit of improved specificity of cough detection. Experiments are conducted on 45 subjects and CoughTrigger achieved 0.77 AUC score. We also validated its effectiveness on free-living data and through on-device implementation. © 2022 IEEE

4.
Kidney international reports ; 7(2):S236-S237, 2022.
Article in English | EuropePMC | ID: covidwho-1695432
5.
6.
Kidney International Reports ; 7(2):S236-S237, 2022.
Article in English | PMC | ID: covidwho-1693653
7.
Nephrology Dialysis Transplantation ; 36(SUPPL 1):i269, 2021.
Article in English | EMBASE | ID: covidwho-1402436

ABSTRACT

BACKGROUND AND AIMS: Acute kidney injury is an important finding in COVID-19 patients that can even result in renal replacement therapy. AKI complicates COVID-19 management by making volume management and administering agents with renal clearance challenging tasks. Various reasons have been proposed for the development of acute kidney injury in COVID-19 patients, including multi-organ failure and pre-renal causes, drug toxicity, tubular injury, and invasion of proximal tube podocytes by SARS-CoV-2. Although the development of AKI is not uncommon in COVID-19 patients, several inconsistencies in the literature exist regarding incidence rate and risk factors of acute kidney injury among hospitalized patients. This can be attributed to ethnical variations and methodological differences of studies. Herein we report AKI incidence in hospitalized COVID-19 patients in Baqiyatallah Hospital in Iran and investigate associate factors that can lead to AKI and renal replacement therapy in COVID-19 patients. METHOD: In this cross-sectional study, we investigated medical records and laboratory data of hospitalized COVID-19 patients in Baqiyatallah Hospital in Tehran, Iran, from September 2020 until the end of November. COVID-19 infection was confirmed using polymerase chain reaction (PCR), and only patients with Positive PCR for COVID-19 were included. Furthermore, patients with missing data and unknown past medical history were excluded from this study, and a total of 459 patients were selected. The KDIGO criteria for acute kidney injury were used for evaluating kidney injury in COVID-19 patients. ICU admission and dialysis were according to the Ministry of Health and Medical Education on ICU admission and renal replacement therapy in COVID-19 patients. RESULTS: Of 459 patients with the criteria who were admitted to the hospital (244 male, 213 female, with an average age of 59.57 with SD 14.3), 75 patients (16%) developed acute kidney injury in the course of the disease. The mortality rate in patients with AKI (44%) was significantly higher than other patients (9%). The development of the AKI was significantly associated with the risk of ICU admission and the severe forms of the disease. Furthermore, it was observed that the patients who developed AKI was significantly older and male gender, diabetes (DM), Hypertension (HTN), and Previous history of Chronic kidney disease(CKD) was also significantly associated with developing AKI in COVID-19 patients. Chronic heart failure and ischemic heart disease increased the odds of developing AKI, but it was not significant enough to come up with a conclusion. It was observed that from 75 patients who developed AKI, 22 patients (29%) required renal replacement therapy. Of 22 patients who need dialysis, 14 patients did not survive (mortality rate=63%). The previous history of kidney disease increases the risk of dialysis due to AKI, while no significant association was found between age, gender, DM, HTN, and heart disease with the need for dialysis. CONCLUSION: Results of our study indicate that acute kidney injury can be a major obstacle in managing COVID-19 patients. Patients with older age, previous history of CKD, HTN, and DM should be admitted to the hospital and monitored closely to prevent unfortunate outcomes of this disease.

8.
Kidney International Reports ; 6(4):S45-S45, 2021.
Article in English | PMC | ID: covidwho-1192342
9.
22nd ACM International Conference on Multimodal Interaction, ICMI 2020 ; : 614-619, 2020.
Article in English | Scopus | ID: covidwho-955009

ABSTRACT

Tracking the type and frequency of cough events is critical for monitoring respiratory diseases. Coughs are one of the most common symptoms of respiratory and infectious diseases like COVID-19, and a cough monitoring system could have been vital in remote monitoring during a pandemic like COVID-19. While the existing solutions for cough monitoring use unimodal (e.g., audio) approaches for detecting coughs, a fusion of multimodal sensors (e.g., audio and accelerometer) from multiple devices (e.g., phone and watch) are likely to discover additional insights and can help to track the exacerbation of the respiratory conditions. However, such multimodal and multidevice fusion requires accurate time synchronization, which could be challenging for coughs as coughs are usually concise events (0.3-0.7 seconds). In this paper, we first demonstrate the time synchronization challenges of cough synchronization based on the cough data collected from two studies. Then we highlight the performance of a cross-correlation based time synchronization algorithm on the alignment of cough events. Our algorithm can synchronize 98.9% of cough events with an average synchronization error of 0.046s from two devices. © 2020 ACM.

SELECTION OF CITATIONS
SEARCH DETAIL