Search Results for author: Amir M. Rahmani

Found 11 papers, 0 papers with code

Edge-centric Optimization of Multi-modal ML-driven eHealth Applications

no code implementations4 Aug 2022 Anil Kanduri, Sina Shahhosseini, Emad Kasaeyan Naeini, Hamidreza Alikhani, Pasi Liljeberg, Nikil Dutt, Amir M. Rahmani

Smart eHealth applications deliver personalized and preventive digital healthcare services to clients through remote sensing, continuous monitoring, and data analytics.

Efficient Personalized Learning for Wearable Health Applications using HyperDimensional Computing

no code implementations1 Aug 2022 Sina Shahhosseini, Yang Ni, Hamidreza Alikhani, Emad Kasaeyan Naeini, Mohsen Imani, Nikil Dutt, Amir M. Rahmani

Considering the significant role of wearable devices in monitoring human body parameters, on-device learning can be utilized to build personalized models for behavioral and physiological patterns, and provide data privacy for users at the same time.

BIG-bench Machine Learning Privacy Preserving

Online Learning for Orchestration of Inference in Multi-User End-Edge-Cloud Networks

no code implementations21 Feb 2022 Sina Shahhosseini, Dongjoo Seo, Anil Kanduri, Tianyi Hu, Sung-soo Lim, Bryan Donyanavard, Amir M. Rahmani, Nikil Dutt

To this end, we propose a reinforcement-learning-based computation offloading solution that learns optimal offloading policy considering deep learning model selection techniques to minimize response time while providing sufficient accuracy.

Decision Making Model Optimization +1

Novel Blood Pressure Waveform Reconstruction from Photoplethysmography using Cycle Generative Adversarial Networks

no code implementations24 Jan 2022 Milad Asgari Mehrabadi, Seyed Amir Hossein Aqajari, Amir Hosein Afandizadeh Zargari, Nikil Dutt, Amir M. Rahmani

Continuous monitoring of blood pressure (BP)can help individuals manage their chronic diseases such as hypertension, requiring non-invasive measurement methods in free-living conditions.


Personalized Stress Monitoring using Wearable Sensors in Everyday Settings

no code implementations31 Jul 2021 Ali Tazarv, Sina Labbaf, Stephanie M. Reich, Nikil Dutt, Amir M. Rahmani, Marco Levorato

Since stress contributes to a broad range of mental and physical health problems, the objective assessment of stress is essential for behavioral and physiological studies.

Heart Rate Variability Photoplethysmography (PPG)

An Accurate Non-accelerometer-based PPG Motion Artifact Removal Technique using CycleGAN

no code implementations22 Jun 2021 Amir Hosein Afandizadeh Zargari, Seyed Amir Hossein Aqajari, Hadi Khodabandeh, Amir M. Rahmani, Fadi Kurdahi

A photoplethysmography (PPG) is an uncomplicated and inexpensive optical technique widely used in the healthcare domain to extract valuable health-related information, e. g., heart rate variability, blood pressure, and respiration rate.

Heart Rate Variability Photoplethysmography (PPG)

An End-to-End and Accurate PPG-based Respiratory Rate Estimation Approach Using Cycle Generative Adversarial Networks

no code implementations3 May 2021 Seyed Amir Hossein Aqajari, Rui Cao, Amir Hosein Afandizadeh Zargari, Amir M. Rahmani

In this paper, we present an end-to-end and accurate pipeline for RR estimation using Cycle Generative Adversarial Networks (CycleGAN) to reconstruct respiratory signals from raw PPG signals.

Photoplethysmography (PPG) Respiratory Rate Estimation

Personal Mental Health Navigator: Harnessing the Power of Data, Personal Models, and Health Cybernetics to Promote Psychological Well-being

no code implementations15 Dec 2020 Amir M. Rahmani, Jocelyn Lai, Salar Jafarlou, Asal Yunusova, Alex. P. Rivera, Sina Labbaf, Sirui Hu, Arman Anzanpour, Nikil Dutt, Ramesh Jain, Jessica L. Borelli

Traditionally, the regime of mental healthcare has followed an episodic psychotherapy model wherein patients seek care from a provider through a prescribed treatment plan developed over multiple provider visits.

Management Sociology

The Causality Inference of Public Interest in Restaurants and Bars on COVID-19 Daily Cases in the US: A Google Trends Analysis

no code implementations27 Jul 2020 Milad Asgari Mehrabadi, Nikil Dutt, Amir M. Rahmani

Our results showed for states/territories with higher numbers of daily cases, the historical trends in search queries related to bars and restaurants, which mainly happened after re-opening, significantly affect the daily new cases, on average.

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