ArticleSensors (Basel, Switzerland)2018
Integrated Framework of Load Monitoring by a Combination of Smartphone Applications, Wearables and Point-of-Care Testing Provides Feedback that Allows Individual Responsive Adjustments to Activities of Daily Living.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Eccentric Strength Assessment of Hamstring Muscles with New Technologies: a Systematic Review of Current Methods and Clinical Implications.Sports medicine - open · 2021Pooled it
- Mobile Health (mHealth) Apps in Sport Training: A Scoping Review.Sensors (Basel, Switzerland) · 2026Article
- Hitting the Wall in Marathon Running: An Integrative Psychophysiological and Durability-Based Review.Journal of functional morphology and kinesiology · 2026Review
- Beyond Teleconsultation: Exploring the Role of Mobile Health Technologies in Duchenne Muscular Dystrophy.JMIR formative research · 2026Article
- Wearable Electronic Devices for Alzheimer's Disease Care: A Systematic Review of Applications, Benefits, and Challenges.Health science reports · 2026Review
- Ecological momentary assessment of the stress-recovery process through technology mHealth in sports: a scoping review.BMC sports science, medicine & rehabilitation · 2026Article
- Comparative evaluation of ChatGPT versions in training program design: scientific approach, accuracy, and practical applicability.BMC sports science, medicine & rehabilitation · 2025Article
- Wearable technologies to predict and prevent and heart failure hospitalizations: a systematic review.European heart journal. Digital health · 2025Review
- Monitoring Sleep and Nightly Recovery with Wrist-Worn Wearables: Links to Training Load and Performance Adaptations.Sensors (Basel, Switzerland) · 2025Article
- Attributes, Methods, and Frameworks Used to Evaluate Wearables and Their Companion mHealth Apps: Scoping Review.JMIR mHealth and uHealth · 2024Article
- Teeth Lesion Detection Using Deep Learning and the Internet of Things Post-COVID-19.Sensors (Basel, Switzerland) · 2023Article
- Strengths, weaknesses, opportunities, and threats associated with the application of artificial intelligence in connection with sport research, coaching, and optimization of athletic performance: a brief SWOT analysis.Frontiers in sports and active living · 2023Article
- The proportional distribution of training by elite endurance athletes at different intensities during different phases of the season.Frontiers in sports and active living · 2023Review
- Using Computer Vision to Track Facial Color Changes and Predict Heart Rate.Journal of imaging · 2022Article
- Wearable Devices in Diving: Scoping Review.JMIR mHealth and uHealth · 2022Article
- Editorial: Health and Performance Assessment in Winter Sports.Frontiers in sports and active living · 2021Article
- Virtual Training of Endurance Cycling - A Summary of Strengths, Weaknesses, Opportunities and Threats.Frontiers in sports and active living · 2021Article
- A Discussion on Different Approaches for Prescribing Physical Interventions - Four Roads Lead to Rome, but Which One Should We Choose?Journal of personalized medicine · 2020Article
- Wrist-Worn Wearables for Monitoring Heart Rate and Energy Expenditure While Sitting or Performing Light-to-Vigorous Physical Activity: Validation Study.JMIR mHealth and uHealth · 2020Article
- Smartwatch-Derived Data and Machine Learning Algorithms Estimate Classes of Ratings of Perceived Exertion in Runners: A Pilot Study.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Athletes schedule their training and recovery in periods, often utilizing a pre-defined strategy. To avoid underperformance and/or compromised health, the external load during training should take into account the individual's physiological and perceptual responses. No single variable provides an adequate basis for planning, but continuous monitoring of a combination of several indicators of internal and external load during training, recovery and off-training as well may allow individual responsive adjustments of a training program in an effective manner. From a practical perspective, including that of coaches, monitoring of potential changes in health and performance should ideally be valid, reliable and sensitive, as well as time-efficient, easily applicable, non-fatiguing and as non-invasive as possible. Accordingly, smartphone applications, wearable sensors and point-of-care testing appear to offer a suitable monitoring framework allowing responsive adjustments to exercise prescription. Here, we outline 24-h monitoring of selected parameters by these technologies that (i) allows responsive adjustments of exercise programs, (ii) enhances performance and/or (iii) reduces the risk for overuse, injury and/or illness.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.