Evidence map›Paper›PMID 40363368›Full record

ArticleSensors (Basel, Switzerland)2025

An Open-Source Wearable System for Real-Time Human Biomechanical Analysis.

Zachary Hoegberg, Seth Donahue, Matthew J Major

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Zachary HoegbergDepartment of Physical Medicine & Rehabilitation, Northwestern University, Chicago, IL 60611, USA.ORCID 0009-0009-2070-0681
Seth DonahueDepartment of Physical Medicine & Rehabilitation, Northwestern University, Chicago, IL 60611, USA.ORCID 0000-0002-8387-9887
Matthew J MajorDepartment of Physical Medicine & Rehabilitation, Northwestern University, Chicago, IL 60611, USA.ORCID 0000-0002-2330-4619

Funding

Administration for Community Living, National Institute 458 on Disability, Independent Living and Rehabilitation Research 90SFGE0
6 · The paper itself

Abstract

The advancement of inertial measurement unit (IMU) technology has opened new opportunities for motion analysis, yet its widespread adoption in clinical practice remains constrained by the high costs of proprietary systems, lengthy setup procedures, and the need for specialized expertise. To address these challenges, we present a multi-IMU system designed with streamlined calibration, efficient data processing, and a focus on accessibility for patient-facing applications. Although initially developed for human gait analysis, the modular design of this system enables adaptability across diverse motion tracking scenarios. This work outlines the system's technical framework, including protocols for data acquisition, derivation of gait variables, and considerations for user-friendly software deployment. We further illustrate its utility by measuring lower-limb gait kinematics in near-real time and providing stride-to-stride biofeedback using a single sensor. These initial results underscore the potential of this system for both laboratory-based gait assessment and rehabilitation interventions in clinical environments and future work will assess validation against traditional optical motion capture methods.

Indexed as

Gait AnalysisWearable Electronic DevicesBiomechanical PhenomenaGaitHumansSoftwaregait rehabilitationinertial measurement unitmotion analysiswearable sensors

Identifiers

PMID40363368
PMCPMC12074246

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.