ReviewMicromachines2022
Applications of Smart Material Sensors and Soft Electronics in Healthcare Wearables for Better User Compliance.
Review in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed, 36 citations in OpenAlex.
- Design and Fabrication of a Chitosan-Based Diaphragm Digital Stethoscope for Heart Sound Acquisition.Micromachines · 2026Article
- Mechanical Stability of Amorphous Silicon Thin-Film Devices on Polyimide for Flexible Sensor Platforms.Sensors (Basel, Switzerland) · 2026Article
- Aggregation Periods Influence Step Count Error in Low-Power Wearables.Sensors (Basel, Switzerland) · 2025Article
- Electrostimulation: A Promising New Treatment for Psoriasis.International journal of molecular sciences · 2024Review
- Autophagy and mitophagy as potential therapeutic targets in diabetic heart condition: Harnessing the power of nanotheranostics.Asian journal of pharmaceutical sciences · 2024Review
- Smart Detecting and Versatile Wearable Electrical Sensing Mediums for Healthcare.Sensors (Basel, Switzerland) · 2023Review
- Research on the Factors Affecting the Adoption of Smart Aged-Care Products by the Aged in China: Extension Based on UTAUT Model.Behavioral sciences (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The need for innovation in the healthcare sector is essential to meet the demand of a rapidly growing population and the advent of progressive chronic ailments. Over the last decade, real-time monitoring of health conditions has been prioritized for accurate clinical diagnosis and access to accelerated treatment options. Therefore, the demand for wearable biosensing modules for preventive and monitoring purposes has been increasing over the last decade. Application of machine learning, big data analysis, neural networks, and artificial intelligence for precision and various power-saving approaches are used to increase the reliability and acceptance of smart wearables. However, user compliance and ergonomics are key areas that need focus to make the wearables mainstream. Much can be achieved through the incorporation of smart materials and soft electronics. Though skin-friendly wearable devices have been highlighted recently for their multifunctional abilities, a detailed discussion on the integration of smart materials for higher user compliance is still missing. In this review, we have discussed the principles and applications of sustainable smart material sensors and soft electronics for better ergonomics and increased user compliance in various healthcare devices. Moreover, the importance of nanomaterials and nanotechnology is discussed in the development of smart wearables.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.