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The purpose of this paper is to check an applicability of aluminized basalt fabrics for production of gloves protecting simultaneously against thermal and mechanical factors.

Six variants of protective gloves were manufactured using two different glove constructions: more simple and cheaper with the anatomical thumb arrangement (model A), and more ergonomic one with so called “distance gussets” (model B). Aluminized basalt fabrics were contained in the back side of all variants and in only one variant of palm side. Then the protective properties against thermal and mechanical factors were measured according to the up-to-date standards.

The fulfillment of contact heat requirement was achieved for all glove variants at 100°C. Application of aluminized basalt fabrics in the glove back side allowed obtaining the fourth performance level in the case of resistance to small metal splashes and assuring the highest protection against the radiant heat and small metal splashes. Fulfillment of standard requirements for all examined mechanical parameters was achieved and significantly higher values than reqired for the highest performance level were registered.

The further research including upscalling strategy as well as industrial conditions requirements should be taking into account for basalt textiles development. Moreover functionalization of basalt yarns and fabrics seems to be promising feature.

The preliminary utility trials were done and registered results are very promising, shows that this kind of gloves will be cheaper than produced so far and could be used in the glass, welder companies.

The basalt textiles applied for protective gloves or other personal protective equipment can ensure safety at work for end users operating in mechanical and thermal risk scenarios.

Up till now the basalt fabrics have not been recognized as a material for the personal protective equipment, they were used mostly for technical purposes.

Firefighter Personal Protective Equipment (PPE) is the only barrier between the firefighter and hazardous environment. Gloves are a crucial component of the multi-component PPE. Over time the gloves have reduced the intensity of hand injuries, yet further improvement in terms of material selection and glove design is required to strike the balance between protection and comfort. Focusing on the material aspect, the purpose of this study is to present literature analysis on material selection and testing for firefighter gloves.

The study conducted a literature analysis on material selection and characterization of firefighter PPE. The review summarizes and evaluates past work addressing the characterization of firefighter gloves in accordance with NFPA 1971 requirements and points out found research gaps to aid with foundation of future research.

The study summarizes several research works to inform readers about the material selection and characterization of firefighter gloves. Based on the analyzed literature, the study resulted in material specification sheets for firefighter gloves. The developed material specification sheets provide information in terms of crucial material properties to be incorporated for accurate functioning of firefighter gloves, testing methods to validate those material properties and materials from analyzed literature exhibiting desired properties.

With large research addressing firefighter PPE, only limited studies focus specifically on gloves. Thus, this study provides a literature analysis covering material selection and testing for gloves. A consolidated firefighter gloves material specification document, which does not appear to be available in the literature, will provide a foundation for the development and characterization of firefighter gloves to better serve the functions along with ensuring user comfort.

The purpose of this paper is to present a novel data glove which can capture the motion of the arm and hand by inertial and magnetic sensors. The proposed data glove is used to provide the information of the gestures and teleoperate the robotic arm-hand.

The data glove comprises 18 low-cost inertial and magnetic measurement units (IMMUs) which not only make up the drawbacks of traditional data glove that only captures the incomplete gesture information but also provide a novel scheme of the robotic arm-hand teleoperation. The IMMUs are compact and small enough to wear on the upper arm, forearm, palm and fingers. The calibration method is proposed to improve the accuracy of measurements of units, and the orientations of each IMMU are estimated by a two-step optimal filter. The kinematic models of the arm, hand and fingers are integrated into the entire system to capture the motion gesture. A positon algorithm is also deduced to compute the positions of fingertips. With the proposed data glove, the robotic arm-hand can be teleoperated by the human arm, palm and fingers, thus establishing a novel robotic arm-hand teleoperation scheme.

Experimental results show that the proposed data glove can accurately and fully capture the fine gesture. Using the proposed data glove as the multiple input device has also proved to be a suitable teleoperating robotic arm-hand system.

Integrated with 18 low-cost and miniature IMMUs, the proposed data glove can give more information of the gesture than existing devices. Meanwhile, the proposed algorithms for motion capture determine the superior results. Furthermore, the accurately captured gestures can efficiently facilitate a novel teleoperation scheme to teleoperate the robotic arm-hand.

In this era of globalisation, as competition intensifies, providing quality products and services has become a competitive advantage and a need to ensure survival. The Six Sigma's problem-solving methodology DMAIC has been one of the several techniques used by organisations to improve the quality of their products and services. This paper aims to demonstrate the empirical application of Six Sigma and DMAIC to reduce product defects within a rubber gloves manufacturing organisation.

The paper follows the DMAIC methodology to systematically investigate the root cause of defects and provide a solution to reduce/eliminate them. In particular, the design of experiments, hypothesis testing and two-way analysis of variance techniques were combined to statistically determine whether two key process variables, oven's temperature and conveyor's speed, had an impact on the number of defects produced, as well as to define their optimum values needed to reduce/eliminate the defects.

The analysis from employing Six Sigma and DMAIC indicated that the oven's temperature and conveyor's speed influenced the amount of defective gloves produced. After optimising these two process variables, a reduction of about 50 per cent in the “leaking” gloves defect was achieved, which helped the organisation studied to reduce its defects per million opportunities from 195,095 to 83,750 and thus improve its sigma level from 2.4 to 2.9.

This paper can be used as a guiding reference for managers and engineers to undertake specific process improvement projects, in their organisations, similar to the one presented in this paper.

This study presents an industrial case which demonstrates how the application of Six Sigma and DMAIC can help manufacturing organisations to achieve quality improvements in their processes and thus contribute to their search for process excellence.

To identify the dexterity of spacesuit gloves, they need to undergo bending tests in the development process. The ideal way is to place a humanoid robotic hand into the spacesuit glove, mimicking the motions of a human hand and measuring the bending angle/force of the spacesuit glove. However, traditional robotic hands are too large to enter the narrow inner space of the spacesuit glove and perform measurements. This paper aims to design a humanoid robot hand that can wear spacesuit gloves and perform measurements.

The proposed humanoid robotic hand is composed of five modular fingers and a parallel wrist driven by electrical linear motors. The fingers and wrist can be delivered into the spacesuit glove separately and then assembled inside. A mathematical model of the robotic hand is formulated by using the geometric constraints and principle of virtual work to analyze the kinematics and statics of the robotic hand. This model allows for estimating the bending angle and output force/torque of the robotic hand through the displacement and force of the linear motors.

A prototype of the robotic hand, as well as its testing benches, was constructed to validate the presented methods. The experimental results show that the whole robotic hand can be transported to and assembled in a spacesuit glove to measure the motion characteristics of the glove.

The proposed humanoid robotic hand provides a new method for wearing and measuring the spacesuit glove. It can also be used to other gloves for special protective suits that have highly restricted internal space.

Currently, rehabilitation medical care is expensive, requires a large number of rehabilitation therapist and which can only limit in the fixed location. In addition, there is a lack of research on the structure optimization and theoretical analysis of soft actuators for hand rehabilitation. In view of the problems above, this paper aims to propose a cheap, portable, wearable soft multiple joints rehabilitation glove.

First, this paper determined the hyperelastic constitutive model by material tensile test. Second, the soft actuator’s internal longitudinal section shape was optimized through the comparison of three diverse chamber structures. Meanwhile, the motion model of the soft actuator is established by the finite element model analysis method. Then, this paper established the constitutive model of the soft actuator according to the torque equilibrium equation and analyzed the relationship between the soft actuator’s bending angle and the input air pressure. This paper has verified that the theoretical model is correct through the soft actuator bending test. Finally, rehabilitation gloves were manufactured according to the model and the rehabilitation performance and grasping ability of gloves were verified through experiments.

The optimization results show that the internal semicircular cavity has better performance. Then, the actuator performance is better after adding the external arc structure and optimizing the physical dimension. The experimental results show that the trajectory of the actuator conforms to the mathematical model and rehabilitation gloves can meet the needs of rehabilitation treatment.

Rehabilitation gloves made of actuators can help patients with hand dysfunction in daily rehabilitation training. Then, it can also assist patients with some fine and complicated hand movements.

This paper proposes a new type of soft rehabilitation glove, which is composed of new soft actuators and adapting pieces. The new actuator is small enough to be fitted to the knuckle of the glove to move each joint of the finger.

Two of the emerging issues for the health‐care sector in the 1990s are occupational health and safety, and iatrogenic issues. Both of these issues are implicated in the use of pre‐powdered latex gloves. Hospital healthcare workers are exposed to latex in many ways: gloves, intravenous sets, ventilator circuits, dental products, resuscitation equipment, anaesthetic equipment. Post‐operative complications, delayed wound healing, scar formation, and the potential for misdiagnosis, in the presence of starch powder, have been well documented in the literature with the need for thorough glove rinsing prior to surgery. Another route for glove powder to enter wounds is through a barrier breach. For an institution to ensure it provides the most durable and effective barrier for health‐care worker protection and patient safety, knowledge is needed regarding the various factors which lead to glove barrier failure. The primary aim of the study was to evaluate the in‐use durability of the surgical gloves in current use against powder‐free gloves. Descriptive statistics were used to analyse the data, in addition a cost analysis was calculated. The results of this study demonstrated clinically important differences between existing glove products in terms of barrier quality.

Gesture recognition plays an important role in many fields such as human–computer interaction, medical rehabilitation, virtual and augmented reality. Gesture recognition using wearable devices is a common and effective recognition method. This study aims to combine the inverse magnetostrictive effect and tunneling magnetoresistance effect and proposes a novel wearable sensing glove applied in the field of gesture recognition.

A magnetostrictive sensing glove with function of gesture recognition is proposed based on Fe-Ni alloy, tunneling magnetoresistive elements, Agilus30 base and square permanent magnets. The sensing glove consists of five sensing units to measure the bending angle of each finger joint. The optimal structure of the sensing units is determined through experimentation and simulation. The output voltage model of the sensing units is established, and the output characteristics of the sensing units are tested by the experimental platform. Fifteen gestures are selected for recognition, and the corresponding output voltages are collected to construct the data set and the data is processed using Back Propagation Neural Network.

The sensing units can detect the change in the bending angle of finger joints from 0 to 105 degrees and a maximum error of 4.69% between the experimental and theoretical values. The average recognition accuracy of Back Propagation Neural Network is 97.53% for 15 gestures.

The sensing glove can only recognize static gestures at present, and further research is still needed to recognize dynamic gestures.

A new approach to gesture recognition using wearable devices.

This study has a broad application prospect in the field of human–computer interaction.

The sensing glove can collect voltage signals under different gestures to realize the recognition of different gestures with good repeatability, which has a broad application prospect in the field of human–computer interaction.

Main purpose is to present methodology which allows efficient hand gesture recognition using low-budget, 5-sensor data glove. To allow widespread use of low-budget data gloves in engineering virtual reality (VR) applications, gesture dictionaries must be enhanced with more ergonomic and symbolically meaningful hand gestures, while providing high gesture recognition rates when used by different seen and unseen users.

The simple boundary-value gesture recognition methodology was replaced by a probabilistic neural network (PNN)-based gesture recognition system able to process simple and complex static gestures. In order to overcome problems inherent to PNN – primarily, slow execution with large training data sets – the proposed gesture recognition system uses clustering ensemble to reduce the training data set without significant deterioration of the quality of training. The reduction of training data set is efficiently performed using three types of clustering algorithms, yielding small number of input vectors that represent the original population very well.

The proposed methodology is capable of providing efficient recognition of simple and complex static gestures and was also successfully tested with gestures of an unseen user, i.e. person who took no part in the training phase.

The hand gesture recognition system based on the proposed methodology enables the use of affordable data gloves with a small number of sensors in VR engineering applications which require complex static gestures, including assembly and maintenance simulations.

According to literature, there are no similar solutions that allow efficient recognition of simple and complex static hand gestures, based on a 5-sensor data glove.

Endeavours to determine the physiological and perceptual responses to forearm cold water immersion as influenced by the use of an experimental fireproof carbonaceous insulation (ECI), Thinsulate (a commercial insulation), and Nomex flight gloves. The primary objective was to determine if ECI could provide adequate protection from cold water immersion while providing superior protection from fire. Physiological responses including rectal and skin temperatures to –1 degree C water were recorded. Perceptions of thermal discomfort and grip strength were also measured. The experimental carbonaceous insulation was able to provide better thermal protection as evidenced by significantly higher skin temperatures than the Thinsulate. Subjects perceived the Thinsulate gloves to be only slightly more comfortable than the ECI gloves. Both ECI and Thinsulate provided negligible loss of grip strength. The Nomex gloves provided virtually no thermal protection and substantial loss of grip strength post‐immersion.