Supporting data for “Digital System and Device for AIS Detection and Monitoring: Technical Development with Clinical Validation”

This dataset supports the research presented in the thesis titled “Digital System and Device for AIS Detection and Monitoring: Technical Development with Clinical Validation”. The study aimed to develop and validate two complementary technologies for the management of adolescent idiopathic scoliosis (AIS): (1) the Little Wings smartphone case, a hardware enhancement device designed to improve the accuracy of smartphone‑based angle of trunk rotation (ATR) measurement through mechanical stabilization; and (2) the Infinity Loop flexible posture corrector, a soft brace employing an “∞” configuration to provide comfortable and effective early postural intervention. The dataset encompasses all raw and processed data generated during the two validation studies.

The research involved a total of 61 participants, comprising an AIS group (n=34, age 15.0 ± 3.2 years, 73.5% female) and a healthy control group (n=27, age 23.5 ± 4.1 years). Study 1 (Little Wings validation) used the full cohort (61 participants) to compare ATR measurements obtained with a smartphone alone, a smartphone equipped with the Little Wings case, and the gold‑standard scoliometer. Study 2 (Infinity Loop assessment) involved a subset of 31 AIS patients who underwent immediate postural and functional evaluation using the Kinect Azure RGBD sensor before and after wearing the device. A further subgroup of 21 patients completed additional dynamic function tests (single‑leg balance and 10‑meter walking).

The dataset is organized into a structured folder hierarchy:

- **00_README_AND_DOCUMENTATION/** – Contains the detailed README file and the comprehensive data dictionary (Data_Dictionary.xlsx) that defines all variables, units, and coding schemes.
- **01_RAW_DATA/** – Preserves unprocessed data as originally collected. This includes CSV files of ATR measurements and participant demographics for both studies, as well as the original Kinect Azure RGBD video recordings (.mkv) of static postures, balance tests, and gait tests (pre‑ and post‑intervention). Video files are stored in compressed ZIP archives due to their large size.
- **02_PROCESSED_DATA/** – Contains cleaned, transformed, and aggregated data ready for statistical analysis. For Study 1 this includes merged ATR datasets with left/right rotations converted to signed numerical values, demographic summaries, and stratified analysis results. For Study 2 this includes extracted 3D joint coordinates, the 16 calculated static postural parameters (frame‑by‑frame and participant‑averaged), detailed statistical comparisons (t‑tests, effect sizes), balance and gait metrics (e.g., sway area, path length, step length symmetry), and stratified subgroup analyses (by age, ATR severity, baseline function).
- **03_ANALYSIS_SCRIPTS/** – Provides all Python and C++ scripts used for data processing, coordinate extraction, parameter calculation, and statistical analysis, ensuring full reproducibility.
- **04_Figures/** – Contains all final figures (PNG format) as they appear in the thesis, along with the scripts that generated them.
- **05_SUPPLEMENTARY_MATERIALS/** – Includes ethics approval documentation (Reference: UW22‑270), participant information sheets (Chinese and English versions), detailed device specifications (CAD models, technical drawings), and standard operating procedures for data collection.

All participant identifiers have been removed; subject IDs are anonymized and cannot be traced back to individuals. The dataset provides a comprehensive record of the technical development and clinical validation of the two novel devices, and is intended to enable replication, secondary analysis, and further research into digital AIS management.