Day 8
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Questions and Answers

What was the overall Mean Absolute Percentage Error (MAPE) between lab and watch measurements?

  • 8.1%
  • 5.7% (correct)
  • 10.2%
  • 6.5%

How did the Apple Watch perform compared to other wrist-worn devices during resistance exercises?

  • It was inconsistent and produced unreliable data.
  • It was the least accurate device.
  • It showed favorable results for measuring heart rate. (correct)
  • It overestimated heart rate in all instances.

In runners with a low VO2peak, what was the percentage by which the GF overestimated VO2peak?

  • 7.1% (correct)
  • 6.2%
  • 8.0%
  • 5.7%

What was the result concerning the accuracy of heart rate measurements from the Whoop Band 3.0 during resistance exercises?

<p>They should be interpreted with discretion. (C)</p> Signup and view all the answers

What general conclusion about the accuracy of wearable devices is drawn from the study?

<p>The accuracy of wearable devices varies by activity. (B)</p> Signup and view all the answers

What aspect of physical activity (PA) do current guidelines primarily reflect?

<p>Dose-response relationship (D)</p> Signup and view all the answers

Which type of physical activity is highlighted as being missed by traditional measures?

<p>Vigorous intermittent lifestyle physical activity (B)</p> Signup and view all the answers

What appears to be true about the amount of device-measured PA needed for health benefits?

<p>It is smaller than previously thought. (D)</p> Signup and view all the answers

Vigorously intermittent lifestyle physical activity (VILPA) is characterized by which of the following?

<p>Being integrated into daily life (D)</p> Signup and view all the answers

What does the term 'VILPA' stand for?

<p>Vigorous Intermittent Lifestyle Physical Activity (D)</p> Signup and view all the answers

Why is capturing movement patterns through wearables important?

<p>To identify overlooked sporadic activities. (B)</p> Signup and view all the answers

Which outcome is suggested by the discussion of device-measured PA?

<p>It might aid in reducing certain diseases. (A)</p> Signup and view all the answers

What is a common misconception regarding leisure time exercise?

<p>It is the only beneficial form of PA. (B)</p> Signup and view all the answers

What must training load relate to for it to be meaningful?

<p>An outcome, such as injury occurrence (A)</p> Signup and view all the answers

What does the systematic review by Fuller et al. primarily focus on?

<p>Reliability and validity of wearable devices (C)</p> Signup and view all the answers

Which aspects were evaluated in the reliability and validity study by Fuller et al.?

<p>Steps, heart rate, and energy expenditure (A)</p> Signup and view all the answers

What type of devices are assessed for measuring physical activity metrics according to the content?

<p>Wearable fitness trackers (B)</p> Signup and view all the answers

What do external stressors in training typically vary with?

<p>Noise and performance outcomes (C)</p> Signup and view all the answers

Which factor contributes to the validity of wearable activity trackers?

<p>The accuracy of the data they collect (D)</p> Signup and view all the answers

What was one of the main criticisms of wearable activity trackers as indicated in the content?

<p>Their reliability and marketing claims (A)</p> Signup and view all the answers

What aspect of sleep was mentioned in the provided content?

<p>How restful the sleep experience is (D)</p> Signup and view all the answers

What is the relationship between blood sugar levels and fatigue according to Dr. Michael Riddell?

<p>Blood sugar levels do not directly determine fatigue. (A)</p> Signup and view all the answers

In comparison to indirect calorimetry (IC), how does the Oura Ring's energy expenditure (EE) measurement perform?

<p>It underestimates EE, particularly for sitting and standing. (B)</p> Signup and view all the answers

What was a significant finding about Oura Ring's step count accuracy?

<p>It significantly overestimated step counts. (D)</p> Signup and view all the answers

What factor affects the accuracy of optical heart rate monitors during physical activity?

<p>Motion artifacts caused by hand movements (A)</p> Signup and view all the answers

What limitation does the Oura Ring have according to the study findings?

<p>It cannot be used interchangeably with reference monitors. (D)</p> Signup and view all the answers

During which conditions was the optical heart rate monitor noted to be less accurate?

<p>During vigorous physical activity or underwater (B)</p> Signup and view all the answers

Which activity was particularly noted for high measurement error when using the Oura Ring?

<p>Sitting (C)</p> Signup and view all the answers

What aspect of the Oura Ring's performance was found to correlate strongly with the pedometer?

<p>Step count (A)</p> Signup and view all the answers

What type of signals does the mPower device record?

<p>Surface EMG signals (B)</p> Signup and view all the answers

Which derived metric is NOT associated with the mPower device?

<p>Body temperature (C)</p> Signup and view all the answers

What is the main function of the Mettis device?

<p>Measure foot landing dynamics (D)</p> Signup and view all the answers

Which company manufactures the mPower device?

<p>Fibrux Oy (A)</p> Signup and view all the answers

How does the PUSH device provide feedback during training?

<p>Real-time audio feedback (A)</p> Signup and view all the answers

What type of sensors are used in the Mettis device?

<p>Force and pressure sensors (A)</p> Signup and view all the answers

What is the reliability status of the mPower, Mettis, and PUSH devices?

<p>None of the devices have undergone reliability testing (C)</p> Signup and view all the answers

Which device is connected to a mobile application for data analysis?

<p>All of the above (D)</p> Signup and view all the answers

What is the main goal of descriptive analytics in the context of improving athletic performance?

<p>Understanding the relationship between training intensity and performance improvement (C)</p> Signup and view all the answers

Which consideration is crucial for ensuring the reliability of collected data?

<p>Collecting data based on valid and reliable measures (A)</p> Signup and view all the answers

What does diagnostic analytics focus on in training outcomes?

<p>Establishing causal relationships between training variables (B)</p> Signup and view all the answers

What is the purpose of predictive analytics in the context of endurance training?

<p>To forecast the likelihood of successful training outcomes (C)</p> Signup and view all the answers

Which of the following best describes prescriptive analytics?

<p>Offering several strategies to enhance endurance performance (D)</p> Signup and view all the answers

Which statistical measure is particularly important in diagnostic analytics?

<p>Statistical significance (D)</p> Signup and view all the answers

What type of biases may affect decision-making in prescriptive analytics?

<p>Cognitive biases (C)</p> Signup and view all the answers

How does poor data collection affect analytics outcomes?

<p>It generates misleading conclusions and analysis (B)</p> Signup and view all the answers

Flashcards

Wearable devices

Devices that capture movement patterns, including brief bursts of vigorous activity.

Vigorous intermittent lifestyle physical activity (VILPA)

Brief bursts of vigorous activity integrated into daily life.

Dose–response relationship

The connection between the amount of physical activity and its effect on health outcomes.

Perceived PA levels

An individual's subjective estimation of physical activity.

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Device-measured PA

Physical activity measured using devices like wearables.

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Current PA guidelines

Current recommendations for physical activity.

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Health outcomes

Results or effects on health due to physical activity.

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Actual PA levels

True amount of physical activity performed.

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Wrist-worn device accuracy (VO2)

Wrist-worn devices show variable accuracy in estimating VO2, depending on the activity type and individual metrics like VO2peak.

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MAPE (VO2)

Mean Absolute Percentage Error (MAPE) of VO2 measurements in various studies, comparing wearable devices with lab measurements.

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VO2peak differences

Low VO2peak levels tend to be overestimated by wrist-worn devices, while high VO2peak values are often underestimated.

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Apple Watch HR

Apple Watch heart rate (HR) measurements during exercise are generally reliable for prescribing or monitoring resistance training.

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Whoop Band HR

Heart rate (HR) measurements on the Whoop Band 3.0 during resistance exercises may require careful interpretation due to potential inaccuracies.

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Blood sugar and performance

The relationship between blood sugar levels and athletic performance is complex. Low blood sugar doesn't guarantee fatigue, and high blood sugar doesn't prevent it.

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Continuous glucose monitors (CGMs)

Devices that provide a constant stream of data about blood sugar levels.

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Oura Ring energy expenditure (EE)

The Oura Ring tends to underestimate energy expenditure (EE) compared to other devices, especially during activities like walking and running.

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Oura Ring step count accuracy

The Oura Ring overestimates step count compared to pedometers, but the accuracy is acceptable for basic tracking.

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Optical HRMs in sports

Optical heart rate monitors (HRMs) are less accurate during intense exercise or underwater.

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Motion artifacts

Errors in measurements (like heart rate) caused by movement.

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Comparison of activity levels

Different devices might measure activity levels (energy expenditure, steps) differently.

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Device interchangeability

Oura Ring cannot be used interchangeably for precise measurements in the same way as external devices in a study.

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Training load

The quantity and intensity of exercise a person does over a period.

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Meaningful training load

Training load that is linked to a specific outcome, such as injury risk or performance improvement.

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Variability in training load

Fluctuations in the amount and intensity of exercise from day to day.

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External stress

Factors outside of training that can impact an individual's fitness and performance.

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Validity

The accuracy of a measurement tool in reflecting what it's intended to measure.

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Reliability

The consistency or repeatability of a measurement tool.

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Data access

The ability to obtain and analyze data from wearable devices.

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mPower

A wearable device that uses electrodes to record surface EMG signals, providing insights into muscle activation, fatigue, and timing. It offers metrics like activation power, volume, and fatigue index. Connects to a mobile app.

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Mettis Trainer

Biomechanical shoe insoles with sensors that measure movement parameters like cadence, distance, gait, and force distribution during walking. Provides real-time audio feedback and connects to a mobile app.

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PUSH

A device that uses an accelerometer and gyroscope to record velocity, power, and work during physical activity. It's worn as a strap and captures data for tracking performance and exertion.

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Surface EMG (Electromyography)

A technique that records electrical signals generated by muscle activity using electrodes placed on the skin. These signals reflect muscle activation and fatigue levels.

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Activation Power

A measure of muscle activity, quantifying the intensity and duration of muscle contractions. Represents the energy exerted by the muscle during movement.

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Activation Volume

The total amount of muscle activation during a specific activity, representing the overall muscle workload. It combines activation intensity and duration.

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Active Power Balance

This metric refers to the coordinated activation of different muscle groups, reflecting the balance of muscle effort during a movement. It helps optimize performance and reduce injury risk.

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Fatigue Index

A measurement that quantifies the level of muscle fatigue during exercise, providing insight into how much effort a muscle has expended and its capacity for further activity.

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Conceptual Data Analytics Framework

A structured approach for analyzing data related to athletic performance, encompassing descriptive, diagnostic, predictive, and prescriptive aspects.

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Descriptive Analytics

Describing key athletic performance metrics, such as physical test results or training intensity, to monitor progress.

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Diagnostic Analytics

Investigating the connection between factors like training intensity and improvement in endurance. It helps understand why things are happening.

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Predictive Analytics

Forecasting the probability of future athletic performance outcomes based on planned training and historical data.

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Prescriptive Analytics

Recommending strategies for improving athletic endurance, considering both the data and the athlete's individual needs.

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Data Quality

The accuracy and reliability of the information collected, crucial for meaningful analysis.

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Causation vs. Association

While strong associations may be observed, they don't necessarily prove a causal relationship. Deeper investigation is needed.

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Cognitive Biases

Mental shortcuts that can influence decision-making, which should be acknowledged while using predictive and prescriptive analytics.

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Study Notes

KIN 3110 | Advanced Fitness Assessment

  • Course taught by Robert Gumiak, PhD
  • Course covers wearable technology in fitness assessment

Plan for the Day

  • Recap of previous class/lab
  • Review of an assigned reading
  • Discussion of wearable technology

Key Questions

  • Applications of wearable technology in commercial fitness
  • Applications of wearable technology in exercise
  • Novel applications of wearable technology
  • Recording and storing body data using technology
  • Limitations of wearable technology
  • Wearable technology: smart watches, heart rate monitors
  • Mobile exercise apps
  • Fitness programs for older adults
  • Exercise for weight loss
  • Traditional strength training
  • High-intensity interval training
  • Data-driven training technology
  • Exercise for mental health
  • Functional fitness training
  • Health/wellness coaching
  • Wearable technology
  • Strength training with free weights
  • Body weight training
  • Fitness programs for older adults
  • Functional fitness training
  • Outdoor activities

What are Wearables?

  • Small, portable, lightweight devices
  • Worn on, close to, or in the body
  • Monitor, analyze, transmit, and/or receive data
  • Used by a wide range of individuals

Wearables and Energy Expenditure

  • Accuracy of energy expenditure estimates varies between activities
  • Larger errors are observed from devices using accelerometry alone
  • Adding heart rate sensing improves energy expenditure estimates in most activities
  • Research-grade devices may not be superior to commercial devices in some activity types

Continuous Glucose Monitoring in Athletics

  • CGMs monitor glucose in diabetics
  • Used in non-diabetics to guide pre/during/post exercise CHO intake
  • The link between blood sugar and performance is complex
  • Low blood sugar does not always result in fatigue, and vice versa

Validation of Oura Ring Energy Expenditure and Steps

  • Oura Ring tends to underestimate energy expenditure (EE) compared with reference monitors.
  • Significant errors in sitting, standing, fast walking, and running.
  • Step count correlates strongly with pedometers, but overestimates

Devices for Monitoring Training Loads and Movement

  • mPower: Measures muscle activation
  • Mettis Trainer: Biomechanical shoe insoles to monitor cadence, distance, impact force
  • PUSH: Accelerometer and gyroscope attached to a strap to record velocity, power, and total work

Devices for Monitoring HR and HRV

  • Omega Wave: Heart rate variability, neuromuscular, sensorimotor and physical work capacity
  • MioSlice: Monitors physical activity levels and heart rate
  • HELO: Monitors blood pressure, heart rate, ECG

Devices for Monitoring Sleep

  • Fitbit Flex/Charge2: Wristbands tracking sleep time and time in bed
  • Sleep Shepherd: Fabric headband monitoring EEG signals to reduce brain activity for sleep
  • HUSH: Wireless earplugs connected to a mobile app playing soothing music for sleep
  • Dreampad: Pillow connected to a mobile app playing programmable songs for sleep promotion

Challenges with Wearable Monitoring

  • Accuracy of VO2 estimation (some devices rely on speed/inclination)
  • How EE is measured (use of body mass, age, activity)
  • HR/HRV accuracy (influenced by body temperature and metabolism)
  • "Step" detection and sensitivity thresholds

Validity and Reliability of Wearable Devices

  • There is a risk of errors in device measures for steps, energy expenditure and heart rate

Recommendations for Using Wearable Technology in Sleep and Circadian Research

  • PSG (polysomnography) is the gold standard, but it has drawbacks (cost, personnel, reliance on manual scoring, imperfect inter-rater reliability)
  • Wearable devices need to be carefully validated and accurate, reliable, efficient and measured longitudinally

Limitations of Wearable Technology

  • Only ~5% of wearables are formally validated
  • Algorithms are proprietary
  • Digital 'black box'
  • Imperfect data collection (e.g., weather, stoppages)
  • Cost prohibitive
  • Health inequalities exacerbated

Conceptual Data Analytics Framework

  • Descriptive: Data collection and basic monitoring
  • Diagnostic: Relating training intensity and improvement
  • Predictive: Forecasting training outcomes
  • Prescriptive: Optimal strategies for improving performance
  • Different user types (e.g., well-paid consultant, single mother, technophile informatician)
  • Psycho-social effects of wearable technology use (e.g., motivation, addiction, social pressure)
  • Societal trends related to CHT use (e.g., datafication, economization, individualization)

Considerations

  • Self-diagnosis based on self-gathered data may not be consistent with clinical diagnoses
  • Self-monitoring can reveal undiagnosed health problems but there are also false positives/negatives
  • Continuous monitoring can produce an unhealthy obsession with personal health

Next Class

  • Music in Assessment

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Day 8-KIN3110-2024 Wearable Technology PDF

Description

This quiz explores the applications and limitations of wearable technology in fitness assessment as covered in KIN 3110. Students will discuss the impact of wearable technology and recent fitness trends. Prepare to delve into how technology is shaping fitness practices today.

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