artificial muscle

BACKGROUND: Artificial Intelligence (AI) offers an approach to predictive modeling. The model learns to determine specific patterns of undesirable outcomes in a dataset. Therefore, a decision-making algorithm can be built based on these patterns to prevent negative results. This systematic review aimed to evaluate the usefulness of AI in breast reconstruction. METHODS: A systematic review was conducted in August 2022 following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines...

BACKGROUND: With the in-depth development of assistive treatment devices, the application of artificial knee joints in the rehabilitation of amputees is becoming increasingly mature. The length of residual limbs and muscle strength of patients have individual differences, and the current artificial knee joint lacks certain adaptability in the personalized rehabilitation of patients. PURPOSE: In order to deeply analyze the impact of different types of artificial knee joints on the walking function of unilateral thigh amputees, improve the performance of artificial knee joints, and enhance the rehabilitation effect of patients, this article combines image processing technology to conduct in-depth research on the walking gait analysis of different artificial knee joints of unilateral thigh amputees...

The integration of molecular machines and motors into materials represents a promising avenue for creating dynamic and functional molecular systems, with potential applications in soft robotics or reconfigurable biomaterials. However, the development of truly scalable and controllable approaches for incorporating molecular motors into polymeric matrices has remained a challenge. Here, we show that light-driven molecular motors with sensitive photo-isomerizable double bonds can be converted into initiators for Cu-mediated controlled/living radical polymerization enabling the synthesis of star-shaped motor-polymer conjugates...

Functional tissue-engineered artificial skeletal muscle tissue has great potential for pharmacological and academic applications. This study demonstrates an in vitro tissue engineering system to construct functional artificial skeletal muscle tissues using self-organization and signal inhibitors. To induce efficient self-organization, we optimized the substrate stiffness and extracellular matrix (ECM) coatings. We modified the tissue morphology to be ring-shaped under optimized self-organization conditions...

Soft pneumatic actuators (SPAs) play a crucial role in generating movements and forces in soft robotic systems. However, existing SPA designs require significant structural modifications to be used in applications other than their original design. The present article proposes an omni-purpose fully 3D-printable SPA design inspired by membrane type mold and cast SPAs. The design features a spring-like zig-zag structure 3D-printed using an affordable 3D printer with thermoplastic polyurethane and a minimum wall thickness between 0...

IMPORTANCE: Prior studies demonstrated consistent associations of low skeletal muscle mass assessed on surgical planning scans with postoperative morbidity and mortality. The increasing availability of imaging artificial intelligence enables development of more comprehensive imaging biomarkers to objectively phenotype frailty in surgical patients. OBJECTIVE: To evaluate the associations of body composition scores derived from multiple skeletal muscle and adipose tissue measurements from automated segmentation of computed tomography (CT) with the Hospital Frailty Risk Score (HFRS) and adverse outcomes after abdominal surgery...

Hydrogel actuators with anisotropic structures exhibit reversible responsiveness upon the trigger of various external stimuli, rendering them promising for applications in many fields including artificial muscles and soft robotics. However, their effective operation across multiple environments remains a persistent challenge, even for widely studied thermo-responsive polymers like poly(N-isopropyl acrylamide) (PNIPAm). Current attempts to address this issue are hindered by complex synthetic procedures or specific substrates...

Background: Despite the importance of the deltoid to shoulder biomechanics, very few studies have quantified the three-dimensional shape, size, or quality of the deltoid muscle, and no studies have correlated these measurements to clinical outcomes after anatomic (aTSA) and/or reverse (rTSA) total shoulder arthroplasty in any statistically/scientifically relevant manner. Methods: Preoperative computer tomography (CT) images from 1057 patients (585 female, 469 male; 799 primary rTSA and 258 primary aTSA) of a single platform shoulder arthroplasty prosthesis (Equinoxe; Exactech, Inc...

Electroactive artificial muscles with deformability have attracted widespread interest in the field of soft robotics. However, the design of artificial muscles with low-driven voltage and operational durability remains challenging. Herein, novel biomass porous carbon (BPC) electrodes are proposed. The nanoporous BPC enables the electrode to provide exposed active surfaces for charge transfer and unimpeded channels for ion migration, thus decreasing the driving voltage, enhancing time durability, and maintaining the actuation performances simultaneously...

Body composition assessment plays a pivotal role in understanding health, disease risk, and treatment efficacy. This narrative review explores two primary aspects: imaging techniques, namely ultrasound (US) and dual-energy x-ray absorptiometry (DXA), and the emergence of artificial intelligence (AI) and mobile health apps in telehealth for body composition. Although US is valuable for assessing subcutaneous fat and muscle thickness, DXA accurately quantifies bone mineral content, fat mass, and lean mass. Despite their effectiveness, accessibility and cost remain barriers to widespread adoption...

PURPOSE: Body composition (BC) may play a role in outcome prognostication in patients with gastroesophageal adenocarcinoma (GEAC). Artificial intelligence provides new possibilities to opportunistically quantify BC from computed tomography (CT) scans. We developed a deep learning (DL) model for fully automatic BC quantification on routine staging CTs and determined its prognostic role in a clinical cohort of patients with GEAC. MATERIALS AND METHODS: We developed and tested a DL model to quantify BC measures defined as subcutaneous and visceral adipose tissue (VAT) and skeletal muscle on routine CT and investigated their prognostic value in a cohort of patients with GEAC using baseline, 3-6-month, and 6-12-month postoperative CTs...

Soft robotics is a rapidly growing field that spans the fields of chemistry, materials science, and engineering. Due to the diverse background of the field, there have been contrasting naming schemes such as "intelligent," "smart," and "adaptive" materials, which add vagueness to the broad innovation among literature. Therefore, a clear, functional, and descriptive naming scheme is proposed in which a previously vague name- Soft Material for Soft Actuators -can remain clear and concise- Phase-Change Elastomers for Artificial Muscles ...

BACKGROUND: 'Mo-fi-disc' is a new scoring system that quantifies degeneration of the lumbar spine and predicts the intensity of low back pain (LBP). However, its association with LBP-related disability is unknown. In the present study, we aimed to analyze whether 'Mo-fi-disc' scoring system could predict LBP-related disability and distinguish patients with LBP from asymptomatic subjects, while the spine medicine marching towards the era of artificial intelligence (AI). METHODS: This is a cross-sectional analysis of a prospectively collected database...

BACKGROUND:  This review discusses the quantitative assessment of tissue composition in the human body (body composition, BC) using radiological methods. Such analyses are gaining importance, in particular, for oncological and metabolic problems. The aim is to present the different methods and definitions in this field to a radiological readership in order to facilitate application and dissemination of BC methods. The main focus is on radiological cross-sectional imaging. METHODS:  The review is based on a recent literature search in the US National Library of Medicine catalog (pubmed...

Flexible piezoresistive pressure sensors have received great popularity in flexible electronics due to their simple structure and promising applications in health monitoring and artificial intelligence. However, the contradiction between sensitivity and detection range limits the application of the sensors in the medium-pressure regime. Here, a flexible piezoresistive pressure sensor is fabricated by combining a hierarchical spinous microstructure sensitive layer and a periodic microsphere array spacer. The sensor achieves high sensitivity (39...

Thermally driven fiber actuators are emerging as promising tools for a range of robotic applications, encompassing soft and wearable robots, muscle function restoration, assistive systems, and physical augmentation. Yet, to realize their full potential in practical applications, several challenges, such as a high operational temperature, incorporation of intrinsic self-sensing capabilities for closed-loop feedback control, and reliance on bulky, intricate actuation systems, must be addressed. Here, an Ag nanoparticles-based twisted and coiled fiber actuator that achieves a high contractile actuation of ≈36% is reported at a considerably low operational temperature of ≈83 °C based on a synergistic effect of constituent fiber elements with low glass transition temperatures...

The body mass index (BMI) is a longstanding, simple, and cost-effective tool for classifying individuals by weight, useful for rapidly screening populations for obesity-related health risks. However, its failure to account for muscle mass, bone density, and fat distribution can lead to misclassifications. This editorial explores the transformative potential of artificial intelligence (AI) in redefining or potentially replacing BMI as a tool for enhancing weight management strategies. Furthermore, it illustrates how AI can offer personalized health assessments, predictive analytics, and tailored interventions, overcoming BMI's shortcomings...

This study investigates the characteristics of a novel origami-based, elastomeric actuator and a soft gripper, which are controlled by hand gestures that are recognized through machine learning algorithms. The lightweight paper-elastomer structure employed in this research exhibits distinct actuation features in four key areas: (1) It requires approximately 20% less pressure for the same bending amplitude compared to pneumatic network actuators (Pneu-Net) of equivalent weight, and even less pressure compared to other actuators with non-linear bending behavior; (2) The control of the device is examined by validating the relationship between pressure and the bending angle, as well as the interaction force and pressure at a fixed bending angle; (3) A soft robotic gripper comprising three actuators is designed...

Bilayer hydrogel actuators, consisting of an actuating layer and a functional layer, show broad applications in areas such as soft robotics, artificial muscles, drug delivery and tissue engineering due to their inherent flexibility and responses to stimuli. However, to achieve the compatibility of good stimulus responses and high mechanical properties of bilayer hydrogel actuators is still a challenge. Herein, based on the double-network strategy and using the synchronous ultraviolet (UV) polymerization method, an upper critical solution temperature (UCST)-type bilayer hydrogel actuator was prepared, which consisted of a poly(acrylamide-co-acrylic acid)[MC] actuating layer and an agar/poly(N-hydroxyethyl acrylamide-co-methacrylic acid)[AHA] functional layer...

Myasthenia gravis (MG) is a rare, autoimmune, antibody-mediated, neuromuscular disease. This study analyzed digital conversations about MG to explore unprovoked perspectives. Advanced search, data extraction, and artificial intelligence-powered algorithms were used to harvest, mine, and structure public domain digital conversations about MG from US Internet Protocol addresses (August 2021 to August 2022). Thematic analyses examined topics, mindsets, and sentiments/key drivers via natural language processing and text analytics...