ArticleSensors (Basel, Switzerland)2025
Validity of a Single Inertial Measurement Unit to Measure Hip Range of Motion During Gait in Patients Undergoing Total Hip Arthroplasty.
Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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
1 citing paper in PubMed.
- Walking with a Passive Hip Exoskeleton and Wearables: Gait Characteristics and Metabolic Power in Senior Adults.Sensors (Basel, Switzerland) · 2025Trial
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Hip flexion range of motion (ROM) during gait is an important surgery outcome for patients undergoing total hip arthroplasty (THA) that could help patient monitoring and rehabilitation. To allow systematic measurements during patients' clinical pathways, hip ROM measurement should be as simple and cheap as possible to ensure patient and clinician acceptance. Single IMU options can match these requirements and offer measurements both during daily living conditions and standardized clinical tests (e.g., 10 m walk, timed up-and-go). However, single-IMU approaches to measure hip ROM have been limited. Thus, the objective of this study was to explore the accuracy of one IMU in measuring hip ROM during gait and to determine whether a single-IMU approach can provide results comparable to those of multi-IMU systems. To assess this, machine learning models were employed, ranging from the simplest (linear regression) to more complex approaches (artificial neural networks). Eighteen patients undergoing THA and seven controls were measured using a 3D opto-electronic motion capture system and one thigh-mounted IMU. Hip ROM was predicted from thigh ROM using regression and classification models and was compared to the reference hip ROM. Multiple regression was the best-performing model, with limits of agreement (LoA) of ±13° and a systematic bias of 0. Random forest, RNN, GRU and LSTM models yielded LoA ranges > 27.8°, exceeding the threshold of acceptable error. These results showed that one IMU can measure hip ROM with errors comparable to those of two-IMU methods, with potential for improvement. Using multiple linear regression was sufficient and more appropriate than employing complex ANN models. This approach offers simplicity and acceptance to users in clinical settings.
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Registered trials
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