About movementa
movementa is a performance lab for athletes. It pairs evidence-based mental-performance protocols with movement analysis — climbing being the flagship computer-vision module — so what gets measured in the field and what gets trained off it sit inside one coherent framework, across disciplines.
1. The five performance factors
We anchor our model on Memmert's (2013) framework of the five performance factors in sport: Constitution shapes the four interacting downstream factors — Technique, Tactics, Fitness, and Cognition. None of them produces output on its own; each arrow in the diagram below represents a real interaction we can train, measure, or impair.
Adapted from Memmert (2013), in Memmert & Raab (Eds.), Sportspsychologie.
For example, in climbing Technique and Fitness are visible — they're what video, force plates and hangboards measure. Tactics and Cognition are largely invisible, yet they decide whether a trained body can deliver under pressure.
Movementa's purpose is to make those two invisible factors visible, trainable, and trackable alongside the physical ones.
2. Why mental performance is non-optional
Cognitive fitness (attention, working memory, decision-making, motor planning) and emotional regulation (anxiety, arousal, self-compassion, appraisal) are not "soft" addenda to physical training — they are throughput multipliers. Empirically, mental-performance interventions in elite sport produce small-to-moderate improvements that compound over a season (Lochbaum et al., 2022; Brown & Fletcher, 2017).
In the case of climbing, for example:
"psychological aspects such as problem-solving ability, movement sequence recall, route finding, self-efficacy and stress management may be better predictors of climbing performance than physiological or biomechanical parameters (e.g., Giles et al., 2006; MacLeod et al., 2007; Morrison & Schöffl, 2007)."
On a single climb, this shows up concretely:
- Beta retention draws on visuospatial working memory (Boschker et al., 2002).
- Coarticulation of moves depends on motor planning depth and chunking — a cognitive resource.
- Pacing and rest selection are intertemporal decisions under fatigue (delay discounting).
- Choke resistance at the crux depends on attentional focus and appraisal of demands vs. resources.
3. The competition arc — three phases movementa covers end-to-end
Pre-competition preparation
Before the season or session: IZOF profiling (Hanin) to find your individual zone of optimal functioning, MAC training (Mindfulness-Acceptance-Commitment; Gardner & Moore, 2007; Josefsson et al., 2019) for attentional control, grit and self-compassion baselining (Duckworth, 2007; Neff, 2003), Brain Endurance Training (Marcora) to inoculate against mental fatigue, and visualisation / beta memorisation drills. Sleep architecture and voice/HR biomarkers calibrate readiness.
In-competition — including choke avoidance
In the moments before and during the climb: a CSAI-2R check-in (Cox, Martens & Russell, 2003; revised from Martens, Vealey & Burton, 1990) flags whether cognitive anxiety, somatic anxiety, or low self-confidence is the limiter; the Challenge vs Threat appraisal (Blascovich & Mendes, 2000; Jones et al., 2009 TCTSA) gates entry — if resources don't meet demands, a 90-second resource-activation reframe runs before you step on. Coping-Effectiveness Training (Lazarus & Folkman, 1984) and thought-probe mid-attempt protocols address the well-documented choking mechanism (Beilock & Carr, 2001): under pressure, attention shifts inward to skill execution, disrupting automaticity. movementa's protocols pull attention back outward onto task-relevant cues.
Recovery and consolidation
Post-session: perceived-performance check-in, self-compassion break (Neff & Germer), sleep architecture tracking, rPPG heart-rate variability and voice biomarker stress recovery (Boersma, 1993; Verkruysse et al., 2008; Elgendi, 2012). The dashboard turns repeated check-ins and performance data into trends.
4. How the app's activities map onto the framework
| Memmert factor | movementa activities |
|---|---|
| Fitness | Sleep quality and impact · photoplethysmography heart rate · brain endurance training · recovery trends |
| Cognition | Spatial memory training that can have broad cognitive transfer · impulsivity assessment · information sampling assessment · thought probes · self-compassion exercises |
| Constitution | Individual Zone of Optimal Function · anthropometrics · grit assessment |
| Technique & Tactics climbing video analysis module | Climb video analysis · kinematics (CCI, geometric entropy, path length) · stick-figure overlays · side-by-side comparison · route-aligned epoch comparison · beta planning and deployment (in progress) |
5. References
The full evidence base — every protocol, instrument and citation used across the app — lives in the Methods & sources section below. Key foundational references for this page:
- Memmert, D. (2013). The five performance factors in sport. In Sportpsychologie.
- Beilock, S. L., & Carr, T. H. (2001). On the fragility of skilled performance: What governs choking under pressure? JEP: General, 130(4), 701–725.
- Blascovich, J., & Mendes, W. B. (2000). Challenge and threat appraisals: The role of affective cues. In Feeling and Thinking.
- Jones, M., Meijen, C., McCarthy, P. J., & Sheffield, D. (2009). A Theory of Challenge and Threat States in Athletes. Int. Rev. Sport & Exercise Psychology, 2(2).
- Martens, R., Vealey, R. S., & Burton, D. (1990). Competitive Anxiety in Sport (CSAI-2).
- Cox, R. H., Martens, M. P., & Russell, W. D. (2003). Measuring anxiety in athletics: the revised Competitive State Anxiety Inventory-2. J. Sport & Exerc. Psychol., 25(4), 519–533.
- Terry, P. C., & Munro, A. (2008). Psychometric re-evaluation of the revised version of the Competitive State Anxiety Inventory-2. Proc. 43rd APS Annual Conference.
- Gardner, F. L., & Moore, Z. E. (2007). The Psychology of Enhancing Human Performance: MAC Approach.
- Josefsson, T., et al. (2019). MAC vs PST for elite athletes (RCT). JSPA, 11(2).
- Lazarus, R. S., & Folkman, S. (1984). Stress, Appraisal, and Coping.
- Neff, K. D. (2003). Self-compassion. Self and Identity, 2(2).
- Duckworth, A. L., et al. (2007). Grit: Perseverance and passion for long-term goals. JPSP, 92(6).
- Hanin, Y. L. (2000). Emotions in Sport (IZOF).
- Boschker, M. S. J., Bakker, F. C., & Michaels, C. F. (2002). Memory for the functional characteristics of climbing walls. JMB, 34(1).
- Corsi, P. M. (1972). Human memory and the medial temporal region of the brain. (Doctoral dissertation, McGill).
- Brown, D. J., & Fletcher, D. (2017). Effects of psychological and psychosocial interventions on sport performance: meta-analysis. Sports Medicine, 47.
- Lochbaum, M., et al. (2022). Sport psychology and performance meta-analyses: A systematic review. PLOS ONE.
- Sanchez, X., Henz, J., Martha, C., & Medernach, J. (2024). Psychological Aspects of Elite Performance in New Olympic Disciplines: The Case of Climbing. The Inquisive Mind / Special Issue on Sport Psychology. ⟨hal-04908769⟩
6. Methods & sources
The full evidence base for every activity, metric and instrument surfaced across the app.
Methods & sources
What's actually under the hood, organised by theme so you can see which evidence base supports each part of the app.
Session check-ins, hydration & sport-specific reflection
Instruments used by the Mental Performance Hub's post-session check-ins, hydration self-assessment, and sport-specific reflection cards.
- Psychophysical bases of perceived exertion (Borg CR-10) Borg, 1982 — Medicine & Science in Sports & Exercise, 14(5), 377–381Perceived-effort scale used in the Perceived Performance check-in.
- Attentional focus during endurance performance (thought-probe methodology) Brick, MacIntyre & Campbell, 2014 — Int. Rev. Sport & Exercise Psychology, 7(1), 106–134On-task focus / task-related interference / off-task thinking probe categories.
- The accuracy of a 4-item hydration self-assessment model to classify urine concentration using different cut-offs Wardenaar F.C. et al., 2026 — Sports Nutrition & Metabolism4-item hydration self-assessment (fluid intake, void frequency, morning void volume, urine colour).
- Psychological Aspects of Elite Performance in New Olympic Disciplines: The Case of Climbing Sanchez, Henz, Martha & Medernach, 2024 — The Inquisitive Mind, Special Issue on Sport Psychology (⟨hal-04908769⟩)Rationale for the climbing-specific reflective check-ins (route-finding, self-efficacy, stress management as performance predictors).
- Reflective practice in sport (foundational reference) Cropley, Miles, Hanton & Niven, 2007 — The Sport Psychologist, 21(4), 475–494Sport-specific post-session reflection as a performance tool.
Wearables & activity import
File formats, HRV validity, and chest-strap accuracy behind the Wearable Import card.
- ANT+ / FIT file specification Garmin / ANT+ Alliance.FIT parsing for Garmin, Wahoo and compatible devices.
- Wearable technology for monitoring the training load and stress recovery in athletes (HRV review) Schmidt-Wolf-Gunter, 2020HRV interpretation guardrails for imported wearable data.
- Accuracy of the Polar H10 heart rate sensor for reliable RR interval detection Gilgen-Ammann, Schweizer & Wyss, 2019 — Eur J Appl Physiol, 119(7), 1525–1532Chest-strap RR-interval validation basis for HRV inputs.
Climbing video analysis — kinematics & expert-rater scoring
Primary sources underpinning the coarticulation, geometric-entropy and CM-PAT metrics shown on each session report.
- Whole body coarticulation reflects expertise in sport climbing Maselli A. et al. — J. Neurophysiol. 2024Generalised sliding-window coarticulation (CCI, depth profile, kinematic informativeness).
- Psychophysiological and emotional antecedents of on-sight climbing performance with alterations in style of ascent Giles D. et al. — Physiology & Behavior, 2025Geometric entropy as a movement-efficiency marker; CM-PAT in field use.
- Climbing performance analysis: a novel tool for the assessment of rock climbers' movement performance (CM-PAT) Taylor N., Giles D. et al., 2020Direct basis for the 1–5 CM-PAT rubric (base of support, transitioning, coordination, technique, tactics).
- Movement and stop durations as performance markers in rock climbing Draper N. et al. — Front. Psychol. 2020, 11:902Performatory / explorative move & appropriate / inappropriate stop segmentation.
- 3D analysis of the body centre of mass in rock climbing Sibella F. et al. — Hum. Movement Sci. 2007Geometric-entropy method for hip / COM trajectories.
- Entropy as a global variable of the learning process Cordier P. et al. — Hum. Movement Sci. 1994Theoretical basis for entropy as a movement-learning index.
Climbing video analysis — pose, hold detection & technique scoring
Computer-vision backbones, datasets and scoring frameworks behind the per-session movement scores.
- Camera-based climbing analysis for a therapeutic training system Beyer et al. — CDBME, 2020Markerless video analysis & therapeutic framing.
- Climbing Technique Evaluation by Means of Skeleton Video Stream Analysis MDPI Sensors, 23(19):8216, 2023Skeleton-stream technique evaluation; Balance & joint-quality scoring.
- Towards Automatic Object Detection and Activity Recognition in Indoor Climbing Vrzáková et al. — MDPI Sensors, 24(19):6479, 2024Hold detection + activity recognition pipeline (Technique metric).
- The Way Up: A Dataset for Hold Usage Detection in Sport Climbing Maschek & Schedl — arXiv 2505.12854 (CVPRW 2025)Contact-based hold usage detection; on-route filter & Footwork.
- ClimbingCap: Multi-Modal Dataset and Method for Rock Climbing in World Coordinate Yan et al. — CVPR 2025World-coordinate kinematics; Power metric.
- Automatic Climbing Move Detection from Fixed-Camera Bouldering Videos IEEE 11264775Move-event detection from pose + image features.
- Design Study of a Data Analysis Tool for Lead Climbing Fruchard et al.Lead-climbing analytics UX patterns.
- Evaluation of Smartphone Camera Positioning on AI Pose Estimation Accuracy JMIR mHealth, 2026, e82412Camera-placement guidance on the upload screen.
- ClimBEiT: ViT-Based Limb Movement Prediction for Visual-Impairment Guidance Cardenas, Semwal et al.Limb-prediction priors; accessibility for visually impaired climbers.
- YOLO vs Edge Detection for Climbing Hold Detection DiVA thesis 1955778Hold-detector tradeoffs (YOLO-with-edge-fallback design).
- Determinants for success in climbing: A systematic review J. Exer. Sci. & Fitness, 2019Jerk coefficient & biomechanical determinants used in Efficiency scoring.
- Morphology of male world cup and elite bouldering athletes Frontiers in Sports and Active Living, 2025, 1588414Anthropometric priors for ape-index estimation & Power calibration.
- Probability model of rock climbing recognition (sensor time series) EURASIP JASP, 2021Time-series fusion of frame evidence.
- Development of a climbing performance analysis tool using computer vision Plymouth Student Scientist, 2024Vision-based scoring framework.
- Pose backbones — MediaPipe Pose, OpenPose, SLEAP Google / CMU / PrincetonMarkerless pose estimation; MediaPipe runs in-browser.
- Lovable AI Gateway — Google Gemini 2.5 / OpenAI GPT-5 (vision) Google / OpenAI / LovableMultimodal models orchestrating the structured analysis.
Adaptive / paraclimbing
Category taxonomy used to tailor feedback for adaptive athletes.
- IFSC Paraclimbing categories International Federation of Sport ClimbingAdaptive category taxonomy.
Brain endurance & cognitive-load training
Two-task cognitive protocols behind the Skills hub Brain Endurance Training (BET).
- Prior brain endurance training improves endurance exercise performance Staiano, Merlini, Romagnoli, Kirk, Ring & Marcora — Eur J Sport Sci. 2023;23(7):1269–1278Two-task BET protocol (incongruent Stroop + 2-back).
- Brain Endurance Training (additional) JSC 2024; PMC 36475378Cognitive-load training rationale.
- Measuring the Reliability of a Gamified Stroop Task: Quantitative Experiment Wiley, Camacho-Hernandez, Lourenco, Bhagat & Shah — JMIR Serious Games 2024;12:e50315Gamified-Stroop modifier: per-trial RT/correct feedback, fastest-RT record, ±5 points, +25 bonus for new fastest, points progress bar.
Mental performance — anxiety, confidence & self-compassion
Validated inventories and interventions in the Mental Performance and Self-compassion modules.
- Competitive State Anxiety Inventory-2 (CSAI-2) Martens, Vealey & Burton, 1990Original 27-item pre-competition inventory (cognitive anxiety, somatic anxiety, self-confidence) — historical basis for the CSAI-2R.
- Measuring anxiety in athletics: the revised Competitive State Anxiety Inventory-2 (CSAI-2R) Cox, Martens & Russell — J. Sport & Exerc. Psychol. 2003, 25(4), 519–533Revised 17-item CSAI-2R used in-app — subscale = mean × 10 (range 10–40).
- Psychometric re-evaluation of the revised version of the Competitive State Anxiety Inventory-2 Terry & Munro — Proc. 43rd APS Annual Conference, 2008Independent factor-structure confirmation supporting adoption of the CSAI-2R over the original CSAI-2.
- On-Sight and Red-Point Climbing: Changes in Performance and Route-Finding Ability Draper et al. — Front. Psychol. 2020, 11:902Climbing-specific application of CSAI-2 across on-sight vs. red-point.
- Self-compassion to decrease performance anxiety in climbers (RCT) Redalyc 6778/677871911004Basis for the self-compassion module sequence.
- Individual Zones of Optimal Functioning (IZOF) HaninPersonalised emotion-performance mapping (Profile).
- Self-compassion, stress, and coping in elite climbers (RCT) Röthlin et al. — Current Issues in Sport Science, 2021, 6Climber-specific self-compassion intervention used as the module backbone.
- Applying self-compassion in sport: An intervention with women athletes Mosewich, Crocker, Kowalski & DeLongis — J. Sport Exerc. Psychol. 2013, 35(5), 514–524Evidence base for self-compassion psychoeducation in athletes.
- Self-compassion and reactions to unpleasant self-relevant events Leary, Tate, Adams, Allen & Hancock — J. Pers. Soc. Psychol. 2007, 92(5), 887–904Foundational self-compassion mechanism.
- The Compassionate Mind / Compassion-Focused Therapy Gilbert, 2009, 2010Threat / soothe / drive systems framing.
- Self-Compassion: An alternative conceptualization of a healthy attitude toward oneself Neff, 2003 — Self and Identity, 2(2), 85–101Three-facet model (kindness, common humanity, mindfulness).
- Hanin's IZOF model — Emotions and athletic performance Hanin, 1997 (Eur Yearbook Sport Psychol, 1, 29–72); 2007 (Handbook of Sport Psychology, 3rd ed.)Optimal/dysfunctional intensity bands per emotion (IZOF Profiler).
- The struggle of giving up personal goals: Affective, physiological, and cognitive consequences of an action crisis Brandstätter, Herrmann & Schüler — J. Pers. Soc. Psychol. 2013, 104(3), 524–541Foundational ACRISS validation in marathon runners: high action-crisis two weeks pre-race predicted elevated cortisol and a measurable race-performance drop. Basis for the 10–14 day pre-event ACRISS window used in the Peak phase.
- The psychophysiological regulation of pacing behaviour and performance: A comprehensive review Venhorst, Micklewright & Noakes — Sports Med. 2018, 48, 2483–2505Confirms ACRISS internal reliability (α = .83–.89) in endurance and positions the action crisis as a psychophysiological regulator of pacing — the mechanism behind ACRISS as an early 'letting-go' signal.
- 'Falling behind,' 'letting go,' and being outsprinted as distinct features of pacing in distance running Venhorst et al. — Int. J. Sports Physiol. Perform. 2021Distinguishes the physical state ('falling behind') from the psychological crisis ('letting go') using the ACRISS framework in elite distance running — informs the ACRISS subscale interpretation in the dashboard chart.
- The psychology of athletic tapering in sport: A scoping review Stone, Knight, Hall, Shearer, Nicholas & Shearer — Sports Medicine 2023, 53(4), 777–801Scoping review of taper psychology that identifies goal-conflict monitoring (including ACRISS-type action-crisis assessment) among the instruments used to check whether a taper is restoring motivation or leaving the athlete in a pre-competition goal crisis — basis for the Taper-phase ACRISS re-administration.
Mindfulness, acceptance & values (MAC)
Mindfulness-Acceptance-Commitment protocol and its acceptance-and-commitment foundations in the MAC Training module.
- The psychology of enhancing human performance: The Mindfulness-Acceptance-Commitment (MAC) approach Gardner & Moore, 2007 — SpringerOriginal MAC manual; 7-module curriculum.
- Mindfulness-Acceptance-Commitment-based approach to athletic performance enhancement Moore — JCSP, 2009, 3(4), 291–302Clinical case formulation of MAC.
- Mindfulness-Acceptance-Commitment (MAC) versus Psychological Skills Training (PST) for elite athletes (RCT) Josefsson, Tornberg, Gustafsson & Ivarsson, 2019 — JSPA 11(2)7-week RCT showing MAC > PST on mindfulness and performance.
- Effectiveness of MAC on athletic performance: A systematic review Wong, How & Cheong, 2022 — Front. Psychol. 13:906729Identifies values-clarification as the active ingredient.
- Acceptance and Commitment Therapy (ACT), 2nd ed. Hayes, Strosahl & Wilson, 2012 — GuilfordCognitive defusion techniques used in the MAC defusion player.
Coping, appraisal & challenge–threat states
Transactional coping and biopsychosocial challenge/threat models behind the CET and Challenge–Threat Appraisal modules.
- Personal control and stress and coping processes: A theoretical analysis Folkman, 1984 — J. Pers. Soc. Psychol., 46(4), 839–852Controllability-based appraisal — the CET branch choice.
- Stress, Appraisal, and Coping Lazarus & Folkman, 1984 — SpringerTransactional model underlying CET.
- Coping Effectiveness Training (CET) — a brief intervention Chesney et al., 2003 — Br. J. Health Psychol., 8(3), 257–272Direct basis for the CET module structure.
- Challenge and threat appraisals: The role of affective cues Blascovich & Mendes, 2000Biopsychosocial model of challenge vs. threat.
- Challenge and threat states (CTSA): Scale validation Searle & Auton, 2015 — Anxiety, Stress & Coping, 28(2), 121–139Demand–resource sliders calibration.
- A Theory of Challenge and Threat States in Athletes (TCTSA) Jones, Meijen, McCarthy & Sheffield, 2009 — Int. Rev. Sport Exerc. Psychol., 2(2), 161–180Sport-specific TCTSA used for reframing prompts.
Interoception & paced breathing
Resonance-frequency breathing and interoceptive awareness scaffolding in the Interoception Training module.
- Heart rate variability biofeedback: How and why does it work? Lehrer & Gevirtz, 2014 — Front. Psychol., 5:7560.1 Hz resonance breathing pacer rationale.
- The Multidimensional Assessment of Interoceptive Awareness, Version 2 (MAIA-2) Mehling et al., 2018 — PLoS ONE, 13(12), e0208034Somatic labelling prompts at 30 / 60 / 90 s.
Sleep & decision-making
Sleep architecture self-report and the link from sleep loss to risky decision-making (Sleep Architecture + Decision Latency Gate).
- DCCASP: Daily Cognitive-Communication & Sleep Profile Turkstra et al., 20207-item daily sleep / fatigue / cognition self-report.
- Why We Sleep: Unlocking the Power of Sleep and Dreams Walker, 2017 — ScribnerSleep and decision-making framing.
- Effects of sleep deprivation on cognition Killgore, 2010 — Progress in Brain Research, 185, 105–129Vulnerability multiplier for the Decision Latency Gate.
Decision-making — delay discounting & mouse-tracking
Mouse-tracked intertemporal choice task in Skills (Delay Discounting).
- Harder than expected: Increased conflict in clearly disadvantageous delayed choices in a computer game Scherbaum, Dshemuchadse, Leiberg & Goschke, 2013 — PLoS ONE 8(11), e79310Task design and trajectory analyses (Figs. 2–4 + Text S1).
- An adjusting procedure for studying delayed reinforcement Mazur, 1987 — in Commons et al. (Eds.), Quantitative analyses of behavior, Vol. 5Hyperbolic k indifference-point fit.
- Continuous dynamics in real-time cognition Spivey & Dale, 2006 — Current Directions in Psychological Science, 15(5), 207–211Foundation for trajectory-based cognition.
- MouseTracker: Software for studying real-time mental processing using a computer mouse-tracking method Freeman & Ambady, 2010 — Behavior Research Methods, 42(1), 226–241MD / AUC trajectory metrics.
- Area under the curve as a measure of discounting Myerson, Green & Warusawitharana, 2001 — J. Exp. Anal. Behav., 76(2), 235–243AUC scoring of the delay-discounting curve.
Reflection–impulsivity — information sampling
Probabilistic information-sampling task with effort cost (Skills · Information Sampling).
- Information sampling and bipolar disorder (beads / boxes task) Clark, Iversen & Goodwin, 2001 — Am. J. Psychiatry, 158(10)Boxes task lineage adapted to athletes.
- Reflection impulsivity in current and former substance users (extended IST paradigm) Clark, Robbins, Ersche & Sahakian, 2006 — Biological Psychiatry, 60(5), 515–522Fixed-win vs. decreasing-win IST variants.
- Reflection-impulsivity in athletes: A cross-sectional and longitudinal investigation Vaughan, Hagyard, Edwards & Jackson, 2020 — Eur J Sport SciSport-specific reflection–impulsivity scoring.
- Adolescents sample more information prior to decisions than adults when effort costs increase Niebaum, Kramer, Huizenga & van den Bos, 2021 — PsyArXivEffort-cost manipulation (low vs high hold time).
- Using posterior P(correct) rather than raw boxes opened to index reflection–impulsivity Bennett, Oldham, Dawson, Parkes, Murawski & Yücel, 2017Posterior-based scoring used in the task readout.
Working memory & beta memorisation
Visuo-spatial working memory paradigms behind Beta Memory and Motion Beta Memory.
- Human memory and the medial temporal region of the brain (Corsi block-tapping) Corsi, 1972 — McGill UniversityCorsi block-tapping span — visuo-spatial WM core.
- The Corsi Block-Tapping Task: standardization and normative data Kessels et al., 2000 — Applied Neuropsychology, 7(4), 252–258Span normative reference.
- Training and plasticity of working memory Klingberg, 2010 — Trends Cogn. Sci., 14(7), 317–324WM training rationale.
- Mental rotation of three-dimensional objects Shepard & Metzler, 1971 — Science, 171(3972), 701–703Mental rotation distractor.
- Memory for the functional characteristics of climbing routes Boschker, Bakker & Michaels, 2002 — J. Sport Exerc. Psychol.Functional-grip memory > visual-only memory.
- The usage of eye-tracking technologies in rock-climbing Grushko & Leonov, 2014 — Procedia Soc. Behav. Sci., 146, 169–174Visual route-preview behaviour.
- The time course of learning a visual skill Karni & Sagi, 1993 — Nature, 365, 250–252Spaced rehearsal rationale.
- Distributed practice in verbal recall tasks Cepeda et al., 2006 — Psychol. Bull., 132(3), 354–380Spacing schedule.
Recovery, stress & biometrics
Subjective recovery scales and physiological signal extraction for the check-in suite.
- Short Recovery & Stress Scale (SRS) Kellmann & Kölling, 2019Recovery / stress check-in form.
- Development of two short measures for recovery and stress in sport Nässi, Ferrauti, Meyer, Pfeiffer, Kellmann — Eur J Sport Sci. 2017Validation reference for the SRS dimensions.
- Algorithmic principles of remote PPG Wang et al., 2017POS-based heart rate from webcam (rPPG).
- Voice biomarkers — pitch, jitter, shimmer, HNR Teixeira & Fernandes, 2014Acoustic feature extraction for voice check-in.
- Remote plethysmographic imaging using ambient light Verkruysse, Svaasand & Nelson, 2008 — Optics Express, 16(26), 21434–21445Foundational rPPG demonstration.
- rPPG-Toolbox: Deep remote PPG toolbox Liu et al., NeurIPS 2024 Datasets & BenchmarksBenchmark pipeline mirrored by RppgRecorder.
- Physiological parameter monitoring from optical recordings with a mobile phone Scully et al., 2012 — IEEE TBME, 59(2), 303–306Smartphone contact-PPG fundamentals (Finger PPG).
- Novel method to detect heart rate from smartphone camera (contact PPG) Pelegris, Banitsas, Orbach & Marias, 2010 — MeMeAFinger-pad PPG signal model.
- Quality assessment of smartphone PPG signals Banerjee et al., 2014 — Healthcare Tech. Letters, 1(2), 74–79Signal-quality gating.
- Comparison of smartphone PPG algorithms vs. reference ECG Nemcova et al., 2020 — Sensors, 20(20), 5972Peak detection / harmonic rejection used in Finger PPG.
- Robust pulse-rate from chrominance-based rPPG de Haan & Jeanne, 2013 — IEEE TBME, 60(10), 2878–2886AC/DC normalisation step.
- Optimal signal quality index for PPG Elgendi, 2012 — Bioengineering, 3(4), 21Quality scoring & doubled-HR mitigation.
- Accurate short-term analysis of the fundamental frequency and harmonics-to-noise ratio of a sampled sound Boersma, 1993 — Proc. IFA, 17, 97–110HNR computation in the voice check-in.
- Speech Science: An Integrated Approach to Theory and Clinical Practice Ferrand, 2002Clinical thresholds for HNR / dysphonia.
- Acoustic correlates of vocal effort and emotion Mendoza et al., 1996; Teixeira et al., 2013/2014Jitter / shimmer reference ranges.
- Articulation rate across the lifespan Jacewicz, Fox & Wei, 2010 — JASA, 128(2), 839–850Speech-rate norm for fatigue / cognitive load.
- Speech and depression / fatigue (AVEC challenges) Cohn et al., 2018 — AVECFatigue-related slowing reference.
- Vocal indicators of emotional stress Giddens et al., 2013 — J. Voice, 27(3), 390.e21–390.e30Stress → F0 / jitter / shimmer direction.
- Voice and breathing under psychosocial stress Van Puyvelde et al., 2018 — Front. Psychol., 9:1494Stress-induced vocal change reference.
- The Speech Behavior of Depressed Individuals: A Review Slavich et al., 2019 — Speech CommunicationSpeech-affect review backing interpretive thresholds.
- Sensors for voice / vocal-effort monitoring (review) Saggio & Costantini, 2020 — Sensors, 20(22), 6573Direction of vocal-feature change under exertion.
- Acoustic analysis of voice under physical exertion Trabelsi & Bouhlel, 2019 — J. VoiceExertion-specific F0 / shimmer / HNR shifts.
Spatial cognition & decision-making (SODT-R)
Dynamic spatial-orientation task adapted into the Skills hub.
- Spatial orientation ability evaluation through a Dynamic Test Santacreu, Rubio & Hernández, 2008 — Personality and Individual Differences, 44(8), 1709–1721Task instructions, 10°-per-press course control, 20 s prediction design.
- Original SODT-R spatial orientation task Santacreu & Rubio, 1998Foundational reflection–impulsivity task adapted in Skills · SODT-R.
- Reflection–impulsivity assessed through performance differences in a computerised spatial task Quiroga, Martínez-Molina, Lozano & Santacreu, 2011 — J. Individual Differences, 32(2), 85–93Scoring of the SODT-R (latency, deviation, RF, QFP) and the Zi reflection–impulsivity index.
Grit & long-term motivation
Trait-grit instrument and climbing-specific evidence behind the Grit module.
- Grit: Perseverance and passion for long-term goals Duckworth, Peterson, Matthews & Kelly, 2007 — J. Personality and Social Psychology, 92(6), 1087–110112-item Grit-O scale (Training & Wellbeing hub).
- Personality, grit and performance in rock-climbing: Down to the nitty-gritty Ionel, Ion & Visu-Petra, 2022 — Int. J. Sport and Exercise PsychologyGrit (perseverance of effort) as a predictor of climbing performance.
- Slumps in elite performance and the role of grit and self-compassion Welch & Tschacher, 2024Grit interpretation during performance slumps.