DOI: 10.5281/zenodo.18755834
title: Dataset - Phase-specific postural adjustments inchildrenand adults duringachallenging balance task

description: ## Overview This repository provides anonymized force-plate derived measures of postural control collected during a modified Can Placement Task (CPT) performed in single-leg stance by two groups: children (9–12 years) and young adults (19–25 years). The task is divided into five phases and performed under two can-position conditions ("closer" and "further"). ## Methods Study design and sample Design: cross-sectional comparison between children and young adults. Participants: 30 typically developing children (9–12 years) and 22 young adults (19–25 years), free from neurological/musculoskeletal/developmental disorders. Screening: children had typical motor development (MABC-2 > 16th percentile); adults confirmed typical health by self-report. Ethics: Institutional approval (Faculty of Physical Culture, Palacký University Olomouc; FTK 46/2020) and informed consent/assent procedures. Data collection protocol (instruments, settings, environment) Task: modified CPT performed in single-leg stance; participants stoop, pick up a can from a low platform, transfer it, place it down, and return to upright stance. Phases (I–V): Phase I: quiet single-leg stance (fixed 3 s) Phase II: stooping to pick up the can Phase III: can transfer (no contact with the can force plate) Phase IV: placing the can down + straightening up Phase V: post-movement stabilization (fixed 3 s) Conditions: closer: can moved toward the participant (backward relative to the second line) further: can moved away (forward beyond the second line; 35 cm distance) Instrumentation: two force platforms (AMTI OR6-5), sampling at 200 Hz, recording COP in AP/ML directions and vertical GRF (including vertical GRF on the can platform). Trials: participants completed familiarization, then 3 successful repetitions per condition per leg, totaling 12 successful trials per participant; analyses used averages across legs. Preprocessing (filters, normalization, anonymization, supported software) Filtering: COP and vertical GRF were filtered with a 4th-order bidirectional low-pass Butterworth filter (10 Hz cutoff). Phase segmentation: phases were identified using the vertical GRF from the can platform; Phase III corresponds to a period with force < 0 N (no contact). Time normalization: each trial was time-normalized using pchip interpolation to a fixed number of samples per phase (600 samples for phases I/II/IV/V and 200 for phase III; 2600 total). Normalization: COP position time series were normalized to participant height using an index based on can movement distance (35 cm) relative to height; GRF was normalized to body weight. Detrending: COP baseline offsets were removed using the mean COP position during Phase I. Time-series summary: for each participant and condition, median time series across repetitions were computed (used for SPM analyses). Software used in original processing/analysis: MATLAB (R2022b), SPM1D (v0.4.10), SPSS (v26). Anonymization: the dataset contains subject IDs only (no direct personal identifiers). Quality control Only successful trials were included (i.e., trials meeting task constraints without loss of balance or rule violations). Participants performed familiarization trials to ensure correct task execution before data collection. ## Data structure Worksheets (tabs) in the Excel file discrete data Participant-level discrete metrics (one row per participant), for both can conditions and multiple task phases. notes Legend for group/condition/direction coding. AP position Time-normalized COP position time series in the anterior–posterior direction (per participant and condition). ML position Time-normalized COP position time series in the medio–lateral direction. AP velocity Time-normalized COP velocity time series in the anterior–posterior direction. ML velocity Time-normalized COP velocity time series in the medio–lateral direction. full spm results Exported arrays used to reproduce/report SPM results across the full normalized timeline. Formats and units Format: Excel .xlsx (tabular numeric data). Discrete measures: derived from filtered/normalized COP and GRF; units are consistent with the paper's reporting conventions for normalized COP measures and relative GRF. Time series: time-normalized arrays (fixed-length sample index across the 5-phase concatenated task; 2600 samples per series). Data dictionary Common identifiers/codes ID: anonymized participant identifier (integer). Group: in discrete data: numeric code (see notes) in time-series sheets: string label (adults / children) plus additional coded columns. Can condition: c = "closer" f = "further" (see notes) Discrete data columns (discrete data sheet) Each metric is provided by phase and condition. COP path length PathLength_phase{1..5}_c PathLength_phase{1..5}_f Mean COP velocity APvel_phase{1..5}_c, APvel_phase{1..5}_f MLvel_phase{1..5}_c, MLvel_phase{1..5}_f COP range APrange_phase{1..5}_c, APrange_phase{1..5}_f MLrange_phase{1..5}_c, MLrange_phase{1..5}_f Maximum relative vertical GRF on the can (support index) max rel GRF phase 2_c, max rel GRF phase 4_c max rel GRF phase 2_f, max rel GRF phase 4_f (phases with can contact as described in the paper) Phase durations (dynamic phases only) Duration_phase2_c, Duration_phase3_c, Duration_phase4_c Duration_phase2_f, Duration_phase3_f, Duration_phase4_f Note: In the provided file, some duration column headers include trailing spaces (e.g., Duration_phase2_c ). This is a formatting artifact; treat them as the same variable name when importing. Time-series sheets (AP position, ML position, AP velocity, ML velocity) The first columns provide identifiers and condition labels (e.g., ID, Group, Can condition, plus additional coded columns). The remaining columns are numbered sample indices (e.g., 1 ... 2600) representing the concatenated, time-normalized task. Missing values If any cells are blank, interpret them as missing (NaN) when importing. (No special missing-value code is defined in notes.) ## Change log - 2026-02-24: First public release on Zenodo ## Contact Ludvík Valtr – ludvik.valtr@upol.cz ACCESS CONDITIONS Access to this record is restricted due to: Ethical restriction. Access may be granted for legitimate research purposes upon reasonable request and subject to approval by the data steward. To request access, please contact: Ludvík Valtr (ludvik.valtr@upol.cz). The request should include:     • brief project description and intended use     • institutional affiliation     • agreement to sign a Data Use Agreement (DUA), if required
description: Funding: This output/paper has been produced with the support of the project ReDiKid: Resilient Kid in Digital World, reg. no. CZ.02.01.01/00/23_025/0008686 co-funded by the EU.