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PODCAST

Physical Activity Researcher

Hello and Welcome to Physical Activity Researcher Podcast! Physical Activity Researcher Podcast is the source of the latest research findings on all things related to physical activity, exercise, and health. World-renowned scientists and experts as guests in an informal and relaxed interview style format. New episodes on Tuesdays, Fridays, and Sundays. The podcast is for anyone who likes to learn scientific and evidence-based knowledge of physical activity, exercise, and health. Our listeners range

science

All Episodes

04:25

Supervised Learning in Physical Activity Research _...

Physical Activity Researcher ·

2025/04/28

🎙️ Supervised Learning in Physical Activity Research – Unlocking Insights from Accelerometry Data How does supervised learning enhance physical activity research? In this episode, we dive into supervised learning, a key machine learning technique that uses labeled data to classify physical activities and predict health outcomes. Learn about: ✔️ How supervised learning processes accelerometer data ✔️ Real-world applications in activity classification and health prediction ✔️ The benefits (high

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17:24

How to Select Participants for an Experience Sampling...

Physical Activity Researcher ·

2025/04/25

🎙️ Selecting the Right Participants for ESM Research – Why It Matters! The success of an ESM study depends on choosing the right participants. Here’s how to do it effectively. In this episode, we discuss key sampling techniques for Experience Sampling Method (ESM) research, including random sampling, stratified sampling, and convenience sampling. Learn how these methods impact data quality, generalizability, and study reliability—and how to balance feasibility with methodological rigor. We’ll also

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44:47

Highlights / How to Measure Sleep? Dr Jesse Cook (Pt2)

Physical Activity Researcher ·

2025/04/23

Jesse Cook is a PhD candidate in the Dr. David Plante Sleep Research Laboratory and studies biological, psychological and sociological factors that connect with unexplained excessive sleepiness. He was first drawn to Alzheimer’s disease (AD) research through the connection between sleep health and AD, and the prevention, detection and potential treatment implications of this connection. Cook believes sleep health disparities across underrepresented groups may help explain disproportionate risk of

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12:47

Overcoming Common Challenges in Experience Sampling...

Physical Activity Researcher ·

2025/04/21

📢 How Can Researchers Overcome Common Challenges in ESM Studies?Participant fatigue, low response rates, and data inconsistencies can threaten ESM research—here’s how to tackle them. In this episode, we explore common challenges in Experience Sampling Method (ESM) research and practical solutions to enhance study success. We discuss strategies to reduce participant fatigue, such as optimizing prompt frequency, personalizing data collection, and offering ethical incentives. Learn how to improve

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16:54

Tricks to Get Better HRV and ECG Signal Quality - How...

Physical Activity Researcher ·

2025/04/14

Does clothing material affect ECG signal quality? José Näf explains how electrostatic effects, electrode placement, and connector design influence long-term HRV and ECG data accuracy. In this second episode, Dr. Olli Tikkanen continues his discussion with José Näf, co-founder of Nahtlos, diving deeper into the practical challenges of long-term ECG and HRV monitoring. José shares critical insights on how connector types, electrode placement, and impedance changes over time affect signal quality. From

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17:06

Wet vs Solid vs Dry Electrodes for HRV – Insights...

Physical Activity Researcher ·

2025/04/11

Dry electrodes often promise convenience, but why do they so often fail in long-term heart monitoring?Jose Naf breaks down the science and business behind electrode design for ECG and HRV tracking. In this episode, Dr. Olli Tikkanen is joined by Jose Naf, founder of Nahtlos, to explore the challenges and innovations in electrode design for long-term ECG and heart rate variability monitoring. Jose shares his entrepreneurial journey from computer vision startups to building advanced medical wearables

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17:23

Highlights / What is Sleep? Dr Jesse Cook (Pt1)

Physical Activity Researcher ·

2025/04/09

Jesse Cook is a PhD candidate in the Dr. David Plante Sleep Research Laboratory and studies biological, psychological and sociological factors that connect with unexplained excessive sleepiness. He was first drawn to Alzheimer’s disease (AD) research through the connection between sleep health and AD, and the prevention, detection and potential treatment implications of this connection. Cook believes sleep health disparities across underrepresented groups may help explain disproportionate risk of

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03:56

Introduction to Machine Learning in Physical Activity...

Physical Activity Researcher ·

2025/04/07

🧠 Can AI Unlock New Insights in Health Research? Machine learning is changing the way we analyze physical activity—revealing patterns and predicting health outcomes like never before. In this episode, we introduce the fundamentals of machine learning (ML) in physical activity and health research. We explore how supervised learning helps classify activities using labeled data, while unsupervised learning uncovers hidden patterns without predefined labels. With the ability to process vast amounts of

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07:36

Illuminating the Future: How Photoplethysmography...

Physical Activity Researcher ·

2025/04/04

💡 Can Light-Based Sensors Revolutionize Health Monitoring?Photoplethysmography (PPG) sensors are reshaping how we track heart health—non-invasively, in real time, and from anywhere. In this episode, we explore how PPG sensors are transforming health monitoring by using light to measure blood flow and cardiovascular function. Once limited to hospital settings, PPG technology is now embedded in wearables, fitness trackers, and medical devices, making real-time heart monitoring more accessible than

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13:39

Highlights / Interesting Ideas How to Analyse Sleep...

Physical Activity Researcher ·

2025/04/02

Christina Reynolds, PhD Christina Reynolds received her Ph.D. in astrophysics from University College London and a Master's degree in software engineering from Harvard University. She has been a Data Scientist with ORCATECH with a focus on developing algorithms for the analysis of ORCATECH's large and diverse data set. Much of her research career has involved developing software algorithms used to fabricate and test the optics for the European Extremely Large Telescope and the IRIS space telescope

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15:41

How to Improve Compliance in Experience Sampling...

Physical Activity Researcher ·

2025/03/31

📢 How Can Researchers Improve Compliance in Experience Sampling Studies? High-quality ESM research depends on participant engagement—so how do we keep compliance rates high without overwhelming them? In this episode, we explore strategies to improve compliance in Experience Sampling Method (ESM) studies, ensuring reliable and high-quality data collection. We discuss the key factors influencing participant motivation, including intrinsic and extrinsic incentives, and how clear communication,

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09:16

How Posture, Activity, HRV data with AI Are Enhancing...

Physical Activity Researcher ·

2025/03/28

🧠 Can AI and Wearables Transform Heart Function Research? From posture to activity levels, new AI-driven insights reveal how daily movements shape cardiovascular health. In this episode, we explore how body position, physical activity, and AI-enhanced HRV data are revolutionizing heart function research. Wearable devices now track posture shifts—sitting, standing, lying down—and physical activity levels in real time, allowing researchers to analyze how these factors influence heart rate and

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28:22

Highlights / Intradaily Variability and Interdaily...

Physical Activity Researcher ·

2025/03/26

Christina Reynolds, PhD Christina Reynolds received her Ph.D. in astrophysics from University College London and a Master's degree in software engineering from Harvard University. She has been a Data Scientist with ORCATECH with a focus on developing algorithms for the analysis of ORCATECH's large and diverse data set. Much of her research career has involved developing software algorithms used to fabricate and test the optics for the European Extremely Large Telescope and the IRIS space telescope

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10:49

Health Insights with Multi-Biosignal Monitoring and...

Physical Activity Researcher ·

2025/03/24

📡 Can Machine Learning Unlock the Full Potential of Wearable Health Data? Multi-biosignal monitoring is revolutionizing research, capturing heart rate variability, ECG, oxygen saturation, and more—now, AI is making sense of it all. In this episode, we explore how machine learning and multi-biosignal monitoring are transforming health research. By combining heart rate variability (HRV), ECG, respiration, body temperature, and movement data, researchers gain a real-world, continuous view of

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07:15

Future Trends and Advancements in Machine Learning...

Physical Activity Researcher ·

2025/03/21

🚀 How Will Machine Learning Shape the Future of Physical Activity Research?From deep learning to real-time feedback, AI is set to transform how we track, analyze, and personalize health insights like never before. In this episode, we explore the future trends and advancements in machine learning for physical activity research. Emerging technologies like deep learning and transfer learning are improving activity recognition, while real-time data processing is making wearables smarter and more

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24:09

Highlights / Why Every Research Team Needs an...

Physical Activity Researcher ·

2025/03/19

Christina Reynolds, PhD Christina Reynolds received her Ph.D. in astrophysics from University College London and a Master's degree in software engineering from Harvard University. She has been a Data Scientist with ORCATECH with a focus on developing algorithms for the analysis of ORCATECH's large and diverse data set. Much of her research career has involved developing software algorithms used to fabricate and test the optics for the European Extremely Large Telescope and the IRIS space telescope

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19:57

Experience Sampling Method (ESM) – Comprehensive...

Physical Activity Researcher ·

2025/03/17

📊 How Can We Capture Human Experience in Real Time? Traditional surveys rely on memory, but what if we could collect thoughts, emotions, and behaviors as they happen? That’s the power of the Experience Sampling Method (ESM). In this episode, we dive into the Experience Sampling Method (ESM)—a research technique that captures momentary experiences, offering deeper insights into human behavior. Unlike retrospective surveys prone to memory bias, ESM gathers real-time data through smartphones, apps,

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06:28

Comparing Supervised and Unsupervised Learning in...

Physical Activity Researcher ·

2025/03/14

🚀 Supervised learning predicts outcomes, while unsupervised learning uncovers hidden trends—but what happens when we combine them? Machine learning is transforming physical activity research, but choosing the right approach can make all the difference. This episode explores the differences between supervised and unsupervised learning in physical activity research, highlighting when to use each method and how they can be combined for more powerful analysis. Supervised learning excels at classifying

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17:34

Highlights / How PA, Sleep and Circadian Rhythm...

Physical Activity Researcher ·

2025/03/12

Dr Anna M Biller is a trained psychologist and neuroscientist, and works at the intersection of light, sleep, circadian rhythms and health psychology. She uses light dosimetry, actimetry, sleep diaries and questionnaires to study health and disease in field studies. She also works on big data derived from wearables. -- This podcast episode is sponsored by Fibion Inc. | Better Sleep, Sedentary Behavior and Physical Activity Research with Less Hassle --- Collect, store and manage SB and PA data

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16:51

Highlights / Sleep Actigraphy: Why Participants...

Physical Activity Researcher ·

2025/03/10

Dr Anna M Biller is a trained psychologist and neuroscientist, and works at the intersection of light, sleep, circadian rhythms and health psychology. She uses light dosimetry, actimetry, sleep diaries and questionnaires to study health and disease in field studies. She is also working with big data derived from wearables.-- This podcast episode is sponsored by Fibion Inc. | Better Sleep, Sedentary Behavior and Physical Activity Research with Less Hassle --- Collect, store and manage SB and PA

en

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