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1. Multimodal Pain Recognition in Postoperative Patients: Machine Learning Approach

2. Establishing the Foundations of Emotional Intelligence in Care Companion Robots to Mitigate Agitation Among High-Risk Patients With Dementia: Protocol for an Empathetic Patient-Robot Interaction Study

3. Physiological and emotional assessment of college students using wearable and mobile devices during the 2020 COVID-19 lockdown: An intensive, longitudinal dataset

4. ZotCare: a flexible, personalizable, and affordable mhealth service provider

5. Longitudinal changes in objective sleep parameters during pregnancy

6. A distinct symptom pattern emerges for COVID-19 long-haul: a nationwide study

7. Objective Prediction of Next-Day’s Affect Using Multimodal Physiological and Behavioral Data: Algorithm Development and Validation Study

8. Personal mental health navigator: Harnessing the power of data, personal models, and health cybernetics to promote psychological well-being

9. A Micro-Level Analysis of Physiological Responses to COVID-19: Continuous Monitoring of Pregnant Women in California

10. Digital Health–Enabled Community-Centered Care: Scalable Model to Empower Future Community Health Workers Using Human-in-the-Loop Artificial Intelligence

11. A Technology-Based Pregnancy Health and Wellness Intervention (Two Happy Hearts): Case Study

12. Continuous Non-Invasive Blood Pressure Monitoring: A Methodological Review on Measurement Techniques

13. Personalized Maternal Sleep Quality Assessment: An Objective IoT-based Longitudinal Study

14. Neural correlates of sparse coding and dimensionality reduction.

15. Long-Term IoT-Based Maternal Monitoring: System Design and Evaluation

16. An Efficient and Robust Deep Learning Method with 1-D Octave Convolution to Extract Fetal Electrocardiogram

17. Investigation of Machine Learning Approaches for Traumatic Brain Injury Classification via EEG Assessment in Mice

18. Neural and Synaptic Array Transceiver: A Brain-Inspired Computing Framework for Embedded Learning

19. Quality-Based Backlight Optimization for Video Playback on Handheld Devices

20. EASYR: <u>E</u> nergy-Efficient <u>A</u> daptive <u>Sy</u> stem <u>R</u> econfiguration for Dynamic Deadlines in Autonomous Driving on Multicore Processors

21. Pregnant in a Pandemic: Connecting Perceptions of Uplifts and Hassles to Mental Health

22. Endurance-Aware Mapping of Spiking Neural Networks to Neuromorphic Hardware

23. Context-Aware Stress Monitoring using Wearable and Mobile Technologies in Everyday Settings

25. The Self-Aware Information Processing Factory Paradigm for Mixed-Critical Multiprocessing

26. Locate: Low-Power Viterbi Decoder Exploration using Approximate Adders

28. Chauffeur: Benchmark Suite for Design and End-to-End Analysis of Self-Driving Vehicles on Embedded Systems

29. Predicting Failures in Embedded Systems Using Long Short-Term Inference

31. ECG Biosignal Deidentification Using Conditional Generative Adversarial Networks

32. SEAMS

34. Label Alignment Improves EEG-based Machine Learning-based Classification of Traumatic Brain Injury

37. Objective Prediction of Next-Day’s Affect Using Multimodal Physiological and Behavioral Data: Algorithm Development and Validation Study (Preprint)

38. Exploring Energy Efficient Architectures for RLWE Lattice-Based Cryptography

39. pyEDA: An Open-Source Python Toolkit for Pre-processing and Feature Extraction of Electrodermal Activity

40. Data Reuse for Accelerated Approximate Warps

41. CAST: Content-Aware STT-MRAM Cache Write Management for Different Levels of Approximation

42. Edge-Assisted Control for Healthcare Internet of Things

43. Embodied Self-Aware Computing Systems

44. Self-Awareness for Autonomous Systems

45. Objective stress monitoring based on wearable sensors in everyday settings

46. Optimizing Energy Efficiency of Wearable Sensors Using Fog‐assisted Control

47. Synthesis of Flexible Accelerators for Early Adoption of Ring-LWE Post-quantum Cryptography

49. Hybrid Learning for Orchestrating Deep Learning Inference in Multi-user Edge-cloud Networks

50. Investigation of Machine Learning and Deep Learning Approaches for Detection of Mild Traumatic Brain Injury from Human Sleep Electroencephalogram

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