4 citations · 6 across the 15 of their papers we have counts for
16 papers
Explainable Prediction from Mobile Sensing Data through LLM-guided Concept Integration
Yuning Wang, Iman Azimi, Amir M. Rahmani +1
Mobile sensing enables longitudinal monitoring of behavioral and physiological patterns in everyday settings. However, accurate prediction remains challenging in small-cohort healt…
TAPAS: Throughput-adaptive Perception for Autonomous Systems
Aman Vyas, Vasista Kodumagulla, Zain Taufique +2
Autonomous systems rely on a perception module to navigate through dynamic environments. In real-world scenarios, the perception module's throughput requirements vary at runtime du…
A Skin-Tone-Aware Dual-Representation Remote Photoplethysmography Framework for Contactless Respiratory Rate Estimation
Trishna Saikia, Anup Kumar Gupta, Puneet Gupta +1
Respiratory rate is a vital indicator of pulmonary and cardiovascular health, yet conventional methods for estimating respiratory rate are often intrusive due to their contact-base…
Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms
Zain Taufique, Aman Vyas, Antonio Miele +2
Compound AI (cAI) systems chain multiple AI models to solve complex problems. cAI systems are typically composed of deep neural networks (DNNs), transformers, and large language mo…
Multimodal Sleep Stage and Sleep Apnea Classification Using Vision Transformer: A Multitask Explainable Learning Approach
Kianoosh Kazemi, Iman Azimi, Michelle Khine +3
Sleep is an essential component of human physiology, contributing significantly to overall health and quality of life. Accurate sleep staging and disorder detection are crucial for…
An LLM-Powered Agent for Physiological Data Analysis: A Case Study on PPG-based Heart Rate Estimation
Mohammad Feli, Iman Azimi, Pasi Liljeberg +1
Large language models (LLMs) are revolutionizing healthcare by improving diagnosis, patient care, and decision support through interactive communication. More recently, they have b…
HiDP: Hierarchical DNN Partitioning for Distributed Inference on Heterogeneous Edge Platforms
Zain Taufique, Aman Vyas, Antonio Miele +2
Edge inference techniques partition and distribute Deep Neural Network (DNN) inference tasks among multiple edge nodes for low latency inference, without considering the core-level…
ECG Unveiled: Analysis of Client Re-identification Risks in Real-World ECG Datasets
Ziyu Wang, Anil Kanduri, Seyed Amir Hossein Aqajari +5
While ECG data is crucial for diagnosing and monitoring heart conditions, it also contains unique biometric information that poses significant privacy risks. Existing ECG re-identi…
Impact of Physical Activity on Quality of Life During Pregnancy: A Causal ML Approach
Kianoosh Kazemi, Iina Ryhtä, Iman Azimi +4
The concept of Quality of Life (QoL) refers to a holistic measurement of an individual's well-being, incorporating psychological and social aspects. Pregnant women, especially thos…
Characterizing Accuracy Trade-offs of EEG Applications on Embedded HMPs
Zain Taufique, Muhammad Awais Bin Altaf, Antonio Miele +2
Electroencephalography (EEG) recordings are analyzed using battery-powered wearable devices to monitor brain activities and neurological disorders. These applications require long…
Robust CNN-based Respiration Rate Estimation for Smartwatch PPG and IMU
Kianoosh Kazemi, Iman Azimi, Pasi Liljeberg +1
Respiratory rate (RR) serves as an indicator of various medical conditions, such as cardiovascular diseases and sleep disorders. These RR estimation methods were mostly designed fo…
Adaptive Workload Distribution for Accuracy-aware DNN Inference on Collaborative Edge Platforms
Zain Taufique, Antonio Miele, Pasi Liljeberg +1
DNN inference can be accelerated by distributing the workload among a cluster of collaborative edge nodes. Heterogeneity among edge devices and accuracy-performance trade-offs of D…
Edge-centric Optimization of Multi-modal ML-driven eHealth Applications
Anil Kanduri, Sina Shahhosseini, Emad Kasaeyan Naeini +4
Smart eHealth applications deliver personalized and preventive digital healthcare services to clients through remote sensing, continuous monitoring, and data analytics. Smart eHeal…
AMSER: Adaptive Multi-modal Sensing for Energy Efficient and Resilient eHealth Systems
Emad Kasaeyan Naeini, Sina Shahhosseini, Anil Kanduri +3
eHealth systems deliver critical digital healthcare and wellness services for users by continuously monitoring physiological and contextual data. eHealth applications use multi-mod…
Optimizing Energy Efficiency of Wearable Sensors Using Fog-assisted Control
Delaram Amiri, Arman Anzanpour, Iman Azimi +4
Recent advances in the Internet of Things (IoT) technologies have enabled the use of wearables for remote patient monitoring. Wearable sensors capture the patient's vital signs, an…
On the Feasibility of Attribute-Based Encryption on Internet of Things Devices
Moreno Ambrosin, Arman Anzanpour, Mauro Conti +4
Attribute-Based Encryption (ABE) could be an effective cryptographic tool for the secure management of Internet-of-Things (IoT) devices, but its feasibility in the IoT has been und…