Evidence map›Paper›PMID 42266453›Full record

ArticleWearable technologies2026

Concerted control framework for human-exoskeleton co-adaptation using ground reaction forces.

Vahid Firouzi, Arjang Ahmadi, Dennis Haufe, Andre Seyfarth, Oskar von Stryk, Rolf Findeisen, Maziar Ahmad Sharbafi

Abstract read
In one paragraph

Article in Wearable technologies, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Vahid FirouziLauflabor Locomotion Laboratory, Centre for Cognitive Science, Sport Science Institute, Technical University of Darmstadt, Darmstadt, Germany.
Arjang AhmadiLauflabor Locomotion Laboratory, Centre for Cognitive Science, Sport Science Institute, Technical University of Darmstadt, Darmstadt, Germany.
Dennis HaufeLauflabor Locomotion Laboratory, Centre for Cognitive Science, Sport Science Institute, Technical University of Darmstadt, Darmstadt, Germany.
Andre SeyfarthLauflabor Locomotion Laboratory, Centre for Cognitive Science, Sport Science Institute, Technical University of Darmstadt, Darmstadt, Germany.
Oskar von StrykSimulation, Systems Optimization and Robotics (SIM) Group, Department of Computer Science,Technical University of Darmstadt, Darmstadt, Germany.
Rolf FindeisenControl & Cyber-Physical Systems Laboratory (CCPS), Department of Electrical Engineering and Information Technology,Technical University of Darmstadt, Darmstadt, Germany.
Maziar Ahmad SharbafiLauflabor Locomotion Laboratory, Centre for Cognitive Science, Sport Science Institute, Technical University of Darmstadt, Darmstadt, Germany.ORCID https://orcid.org/0000-0001-5727-7527

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Effective coordination between the human neuromuscular system and wearable assistive devices remains a key challenge in enhancing gait performance. We propose a concerted control strategy synchronizing biological and artificial actuators using shared feedback. Positioned between centralized (e.g., CPG) and distributed (e.g., reflex-based) control, this approach avoids a central controller by relying on a coordinating signal. Ground reaction force (GRF) emerged as a strong candidate for this role. To implement this concept, we use Force Modulated Compliance (FMC) - a control mechanism that adjusts joint stiffness based on real-time GRF input. FMC has been validated in simulations and robotic platforms, confirming its ability to synchronize joint actuation. We applied this strategy in an active soft biarticular thigh exosuit (BATEX) and tested it in human walking experiments. The GRF-informed controller increased preferred walking speed, advanced the walk-to-run transition, and reduced metabolic cost. These results highlight the effectiveness of GRF-based control in enhancing human-exosuit coordination and aligning assistance with natural gait dynamics. This bioinspired approach offers a scalable framework for real-world locomotion support by harmonizing human and robotic contributions.

Indexed as

controlexosuithuman-in-the-loop-optimizationhuman motor control

Identifiers

PMID42266453
PMCPMC13244345

What Socratic 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 Socratic graph.