Evidence map›Paper›PMID 40843449›Full record

ArticleFrontiers in bioengineering and biotechnology2025

A robot arm-assisted acupuncture system with motion and force monitoring: establishment and validation.

Ying-Chen Li, Yi Yu, Xuan Qiao, Liu-Jie Ren, Jing-Wen Xu, Xin Wang, Wei Gu, Wei Yao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

8 authors.

Ying-Chen Li *Shanghai Key Laboratory of Acupuncture Mechanism and Acupoint Function, College of Biomedical Engineering, Fudan University, Shanghai, China.
Yi Yu *College of Medical Instruments, Shanghai University of Medicine & Health Sciences, Shanghai, China.
Xuan QiaoShanghai Key Laboratory of Acupuncture Mechanism and Acupoint Function, College of Biomedical Engineering, Fudan University, Shanghai, China.
Liu-Jie RenDepartment of Facial Plastic Reconstructive Surgery, Eye and ENT Hospital of Fudan University, Shanghai, China.
Jing-Wen XuShanghai Key Laboratory of Acupuncture Mechanism and Acupoint Function, College of Biomedical Engineering, Fudan University, Shanghai, China.
Xin WangDepartment of Traditional Chinese Medicine, Naval Medical University, Shanghai, China.
Wei GuDepartment of Traditional Chinese Medicine, Naval Medical University, Shanghai, China.
Wei YaoShanghai Key Laboratory of Acupuncture Mechanism and Acupoint Function, College of Biomedical Engineering, Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Traditional manual acupuncture faces challenges in quantifying stimulation parameters and preserving techniques consistency. This study presents a robot arm-assisted acupuncture system replicating manual manipulations with precise motion and force monitoring. Methods: System validation was conducted through a Laser Vibrometer to measure multiple frequency-amplitude combinations, followed by comparative analysis between robotic and manual acupuncture manipulations using both motion and force monitoring. Additionally, therapeutic efficacy was evaluated through an adjuvant arthritis rat model, comparing the analgesic effects between robotic and manual acupuncture at the Zusanli acupoint. Results: The Laser Vibrometer validation showed high precision, with mean absolute errors below 0.2 mm across all frequency-amplitude combinations. Comparative analysis demonstrated strong similarity between robotic and manual acupuncture in needle trajectories and force distributions, with Bhattacharyya coefficients of 0.9931 and 0.9976 for Lifting-Inserting and Mountain Burning manipulations. The robotic system achieved analgesic effects comparable to manual acupuncture, significantly improving pain thresholds over control groups. Conclusion: This work lays the groundwork for quantifiable, reproducible acupuncture therapy, driving the development of intelligent devices for standardized clinical applications.

Indexed as

acupuncture analgesiaacupuncture robot systemadjuvant arthritisinnovation in traditional medicinemotion and force monitoring

Identifiers

PMID40843449
PMCPMC12364822

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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.