Evidence map›Paper›PMID 40606522›Full record

ReviewBME frontiers2025

Soft Robotics for Parkinson's Disease Supported by Functional Materials and Artificial Intelligence.

Hirak Mazumdar, Kamil Reza Khondakar, Suparna Das, Ajeet Kaushik

Abstract readReview
In one paragraph

Review in BME frontiers, 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. Architected Load Paths Enable Stiffening and Motion Programming in Soft Pneumatic Actuators.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    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

4 authors.

Hirak MazumdarDepartment of Computer Science and Engineering, Adamas University, Kolkata, West Bengal 700126, India.
Kamil Reza KhondakarSchool of Science, Woxsen University, Hyderabad, Telangana 502345, India.
Suparna DasDepartment of Computer Science and Engineering, BVRIT HYDERABAD College of Engineering for Women, Hyderabad, Telangana 500090, India.
Ajeet KaushikNanoBioNTech Laboratory, Department of Environmental Engineering, Florida Polytechnic University, Lakeland, FL 33805, USA.ORCID https://orcid.org/0000-0003-4206-1541

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Progressive neurodegenerative disease known as Parkinson's disease (PD) is characterized by both motor and nonmotor symptoms that severely reduce the quality of life. Recent developments in soft robotics provide customizable, cozy, and less intrusive assistive devices, which provide promising answers to these problems. To develop an enhanced support system for people with PD, this article explores the potential of next-generation soft robotics, specifically hydrogel materials, integrated with artificial intelligence (AI) and augmented reality (AR) to provide an innovative solution for PD management. The integration of an AI copilot allows for remote monitoring and real-time adjustments, ensuring optimal performance and personalized care. The use of AR enhances human-computer interactions, offering an intuitive and immersive experience for both patients and healthcare providers. By leveraging these advanced technologies, our approach aims to substantially improve motor function, reduce symptoms, and enhance the overall quality of life for PD patients. This review outlines the key components, benefits, and potential impact of this novel approach, highlighting the transformative potential of combining wearable robotics, AI, and AR in the treatment of PD. The potential for creating novel healthcare solutions by combining soft robotics, functional materials, the Internet-of-Things (IoT), and machine learning (ML) is highlighted by this multidisciplinary approach.

Identifiers

PMID40606522
PMCPMC12214301

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.