Evidence map›Paper›PMID 41013059›Full record

ArticleSensors (Basel, Switzerland)2025

Validity of a Novel Algorithm to Compute Spatiotemporal Parameters Based on a Single IMU Placed on the Lumbar Region.

Giuseppe Prisco, Giuseppe Cesarelli, Maria Romano, Marina Picillo, Carlo Ricciardi, Fabrizio Esposito, Paolo Barone, Mario Cesarelli, Leandro Donisi

Abstract read
In one paragraph

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Giuseppe PriscoDepartment of Medicine and Health Sciences, University of Molise, 86100 Campobasso, Italy.ORCID 0009-0002-1981-5843
Giuseppe CesarelliDepartment of Engineering, University of Naples Parthenope, 80133 Naples, Italy.ORCID 0000-0001-8303-5900
Maria RomanoDepartment of Information Technology and Electrical Engineering, University of Naples Federico II, 80125 Naples, Italy.
Marina PicilloSurgery and Dentistry Scuola Medica Salernitana, Department of Medicine, University of Salerno, 84081 Salerno, Italy.
Carlo RicciardiDepartment of Information Technology and Electrical Engineering, University of Naples Federico II, 80125 Naples, Italy.ORCID 0000-0001-7290-6432
Fabrizio EspositoDepartment of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, 80138 Naples, Italy.ORCID 0000-0002-5099-9786
Paolo BaroneSurgery and Dentistry Scuola Medica Salernitana, Department of Medicine, University of Salerno, 84081 Salerno, Italy.
Mario CesarelliDepartment of Engineering, University of Sannio, 82100 Benevento, Italy.
Leandro DonisiDepartment of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, 80138 Naples, Italy.ORCID 0000-0002-9746-2265

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA single lumbar-mounted inertial sensor offers a practical alternative to optoelectronic systems for gait analysis, simplifying measurements and improving usability in the clinical field. However, its validity can be influenced by sensor placement and signal choice. This study aimed to develop and validate a novel algorithm for estimating spatiotemporal parameters using anteroposterior linear acceleration and angular velocity around the sagittal axis using a single inertial measurement unit (IMU) placed on the lumbar region. The proposed algorithm was validated comparing the parameters computed by the algorithm with the ones computed using a commercial wearable system based on a two-foot-mounted IMU configuration. Thirty healthy subjects underwent a 2 min walk test, and five spatiotemporal parameters were computed using the two methodologies. Study results showed that cadence and gait cycle time exhibited very high agreement, with only a small, statistically significant bias in cadence negligible for practical purposes. In contrast, swing, stance, and double-support parameters showed disagreement due to the presence of systematic proportional errors. This work introduces a novel algorithm for gait event detection and spatiotemporal parameter estimation, addressing uncertainties related to sensor placement, metric models, processing techniques, and signal selection, while avoiding synchronization issues associated with using multiple sensors.

Indexed as

AlgorithmsGait AnalysisLumbosacral RegionAdultBiomechanical PhenomenaFemaleGaitHumansMaleWalkingWearable Electronic DevicesYoung Adultgait analysisgait event detectioninertial measurement unitssensor placementspatiotemporal parameterswearable sensors

Identifiers

PMID41013059
PMCPMC12473921

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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.