Modularity Implications of an Overground Exoskeleton on Plantar Pressures, Strength, and Spasticity in Persons with Acquired Brain Injury.

This study explored the effects of a modular overground exoskeleton on plantar pressure distribution in healthy individuals and individuals with Acquired Brain Injury (ABI). The research involved 21 participants, including ABI patients and healthy controls, who used a unique exoskeleton with adaptable modular configurations. The primary objective was to assess how these configurations, along with factors such as muscle strength and spasticity, influenced plantar pressure distribution. The results revealed significant differences in plantar pressures among participants, strongly influenced by the exoskeleton's modularity. Notably, significant distinctions were found between ABI patients and healthy individuals. Configurations with two modules led to increased pressure in the heel and central metatarsus regions, whereas configurations with four modules exhibited higher pressures in the metatarsus and hallux regions. Future research should focus on refining and customizing rehabilitation technologies to meet the diverse needs of ABI patients, enhancing their potential for functional recovery.

STELO: A New Modular Robotic Gait Device for Acquired Brain Injury-Exploring Its Usability.

In recent years, the prevalence of acquired brain injury (ABI) has been on the rise, leading to impaired gait functionality in affected individuals. Traditional gait exoskeletons are typically rigid and bilateral and lack adaptability. To address this, the STELO, a pioneering modular gait-assistive device, was developed. This device can be externally configured with joint modules to cater to the diverse impairments of each patient, aiming to enhance adaptability and efficiency. This study aims to assess the safety and usability of the initial functional modular prototype, STELO, in a sample of 14 ABI-diagnosed participants. Adverse events, device adjustment assistance and time, and gait performance were evaluated during three sessions of device use. The results revealed that STELO was safe, with no serious adverse events reported. The need for assistance and time required for device adjustment decreased progressively over the sessions. Although there was no significant improvement in walking speed observed after three sessions of using STELO, participants and therapists reported satisfactory levels of comfort and usability in questionnaires. Overall, this study demonstrates that the STELO modular device offers a safe and adaptable solution for individuals with ABI, with positive user and therapist feedback.

Soft gripper for small fruits harvesting and pick and place operations.

Agriculture 4.0 presents several challenges for the automation of various operations, including the fundamental task of harvesting. One of the crucial aspects in the automatic harvesting of high value crops is the grip and detachment of delicate fruits without spoiling them or interfering with the environment. Soft robotic systems, particularly soft grippers, offer a promising solution for this problem, as they can operate in unstructured environments, manipulate objects delicately, and interact safely with humans. In this context, this article presents a soft gripper design for harvesting as well as for pick-and-place operations of small and medium-sized fruits. The gripper is fabricated using the 3D printing technology with a flexible thermoplastic elastomer filament. This approach enables the production of an economical, compact, easily replicable, and interchangeable gripper by utilizing soft robotics principles, such as flexible structures and pneumatic actuation.

Soft Grippers for Automatic Crop Harvesting: A Review.

Agriculture 4.0 is transforming farming livelihoods thanks to the development and adoption of technologies such as artificial intelligence, the Internet of Things and robotics, traditionally used in other productive sectors. Soft robotics and soft grippers in particular are promising approaches to lead to new solutions in this field due to the need to meet hygiene and manipulation requirements in unstructured environments and in operation with delicate products. This review aims to provide an in-depth look at soft end-effectors for agricultural applications, with a special emphasis on robotic harvesting. To that end, the current state of automatic picking tasks for several crops is analysed, identifying which of them lack automatic solutions, and which methods are commonly used based on the botanical characteristics of the fruits. The latest advances in the design and implementation of soft grippers are also presented and discussed, studying the properties of their materials, their manufacturing processes, the gripping technologies and the proposed control methods. Finally, the challenges that have to be overcome to boost its definitive implementation in the real world are highlighted. Therefore, this review intends to serve as a guide for those researchers working in the field of soft robotics for Agriculture 4.0, and more specifically, in the design of soft grippers for fruit harvesting robots.

Multisensory System for the Detection and Localization of Peripheral Subcutaneous Veins.

This paper proposes a multisensory system for the detection and localization of peripheral subcutaneous veins, as a first step for achieving automatic robotic insertion of catheters in the near future. The multisensory system is based on the combination of a SWIR (Short-Wave Infrared) camera, a TOF (Time-Of-Flight) camera and a NIR (Near Infrared) lighting source. The associated algorithm consists of two main parts: one devoted to the features extraction from the SWIR image, and another envisaged for the registration of the range data provided by the TOF camera, with the SWIR image and the results of the peripheral veins detection. In this way, the detected subcutaneous veins are mapped onto the 3D reconstructed surface, providing a full representation of the region of interest for the automatic catheter insertion. Several experimental tests were carried out in order to evaluate the capabilities of the presented approach. Preliminary results demonstrate the feasibility of the proposed design and highlight the potential benefits of the solution.

A research review on clinical needs, technical requirements, and normativity in the design of surgical robots.

Nowadays robots play an important role in society, mainly due to the significant benefits they provide when utilized for assisting human beings in the execution of dangerous or repetitive tasks. Medicine is one of the fields in which robots are gaining greater use and development, especially those employed in minimally invasive surgery (MIS). However, due to the particular conditions of the human body where robots have to act, the design of these systems is complex, not only from a technical point of view, but also because the clinical needs and the normativity aspects are important considerations that have to be taken into account in order to achieve better performances and more secure systems for patients and surgeons. Thus, this paper explores the clinical needs and the technical requirements that will trace the roadmap for the next scientific and technological advances in the field of robotic surgery, the metrics that should be defined for safe technology development and the standards that are being elaborated for boosting the industry and facilitating systems integration.

Novel Robotic Platforms for the Accurate Sampling and Monitoring of Water Columns.

The hydrosphere contains large amounts of suspended particulate material, including living and non-living material that can be found in different compositions and concentrations, and that can be composed of particles of different sizes. The study of this particulate material along water columns plays a key role in understanding a great variety of biological, chemical, and physical processes. This paper presents the conceptual design of two patented robotic platforms that have been conceived for carrying out studies of water properties at desired depths with very high accuracy in the vertical positioning. One platform has been specially designed for operating near to a reservoir bottom, while the other is intended to be used near the surface. Several experimental tests have been conducted in order to validate the proposed approaches.

Intelligent Multisensor Prodder for Training Operators in Humanitarian Demining.

Manual prodding is still one of the most utilized procedures for identifying buried landmines during humanitarian demining activities. However, due to the high number of accidents reported during its practice, it is considered an outmoded and risky procedure and there is a general consensus about the need of introducing upgrades for enhancing the safety of human operators. With the aim of contributing to reduce the number of demining accidents, this paper presents an intelligent multisensory system for training operators in the use of prodders. The proposed tool is able to provide to deminers useful information in two critical issues: (a) the amount of force exerted on the target and if it is greater than the safe limit and, (b) to alert them when the angle of insertion of the prodder is approaching or exceeding a certain dangerous limit. Results of preliminary tests show the feasibility and reliability of the proposed design and highlight the potential benefits of the tool.

A New Approach for Combining Time-of-Flight and RGB Cameras Based on Depth-Dependent Planar Projective Transformations.

Image registration for sensor fusion is a valuable technique to acquire 3D and colour information for a scene. Nevertheless, this process normally relies on feature-matching techniques, which is a drawback for combining sensors that are not able to deliver common features. The combination of ToF and RGB cameras is an instance that problem. Typically, the fusion of these sensors is based on the extrinsic parameter computation of the coordinate transformation between the two cameras. This leads to a loss of colour information because of the low resolution of the ToF camera, and sophisticated algorithms are required to minimize this issue. This work proposes a method for sensor registration with non-common features and that avoids the loss of colour information. The depth information is used as a virtual feature for estimating a depth-dependent homography lookup table (Hlut). The homographies are computed within sets of ground control points of 104 images. Since the distance from the control points to the ToF camera are known, the working distance of each element on the Hlut is estimated. Finally, two series of experimental tests have been carried out in order to validate the capabilities of the proposed method.

VIS-NIR, SWIR and LWIR Imagery for Estimation of Ground Bearing Capacity.

Ground bearing capacity has become a relevant concept for site-specific management that aims to protect soil from the compaction and the rutting produced by the indiscriminate use of agricultural and forestry machines. Nevertheless, commonly known techniques for its estimation are cumbersome and time-consuming. In order to alleviate these difficulties, this paper introduces an innovative sensory system based on Visible-Near InfraRed (VIS-NIR), Short-Wave InfraRed (SWIR) and Long-Wave InfraRed (LWIR) imagery and a sequential algorithm that combines a registration procedure, a multi-class SVM classifier, a K-means clustering and a linear regression for estimating the ground bearing capacity. To evaluate the feasibility and capabilities of the presented approach, several experimental tests were carried out in a sandy-loam terrain. The proposed solution offers notable benefits such as its non-invasiveness to the soil, its spatial coverage without the need for exhaustive manual measurements and its real time operation. Therefore, it can be very useful in decision making processes that tend to reduce ground damage during agricultural and forestry operations.

A new device to automate the monitoring of critical patients' urine output.

Urine output (UO) is usually measured manually each hour in acutely ill patients. This task consumes a substantial amount of time. Furthermore, in the literature there is evidence that more frequent (minute-by-minute) UO measurement could impact clinical decision making and improve patient outcomes. However, it is not feasible to manually take minute-by-minute UO measurements. A device capable of automatically monitoring UO could save precious time of the healthcare staff and improve patient outcomes through a more precise and continuous monitoring of this parameter. This paper presents a device capable of automatically monitoring UO. It provides minute by minute measures and it can generate alarms that warn of deviations from therapeutic goals. It uses a capacitive sensor for the measurement of the UO collected within a rigid container. When the container is full, it automatically empties without requiring any internal or external power supply or any intervention by the nursing staff. In vitro tests have been conducted to verify the proper operation and accuracy in the measures of the device. These tests confirm the viability of the device to automate the monitoring of UO.

Multisensory system for fruit harvesting robots. Experimental testing in natural scenarios and with different kinds of crops.

The motivation of this research was to explore the feasibility of detecting and locating fruits from different kinds of crops in natural scenarios. To this end, a unique, modular and easily adaptable multisensory system and a set of associated pre-processing algorithms are proposed. The offered multisensory rig combines a high resolution colour camera and a multispectral system for the detection of fruits, as well as for the discrimination of the different elements of the plants, and a Time-Of-Flight (TOF) camera that provides fast acquisition of distances enabling the localisation of the targets in the coordinate space. A controlled lighting system completes the set-up, increasing its flexibility for being used in different working conditions. The pre-processing algorithms designed for the proposed multisensory system include a pixel-based classification algorithm that labels areas of interest that belong to fruits and a registration algorithm that combines the results of the aforementioned classification algorithm with the data provided by the TOF camera for the 3D reconstruction of the desired regions. Several experimental tests have been carried out in outdoors conditions in order to validate the capabilities of the proposed system.

Combination of RGB and multispectral imagery for discrimination of cabernet sauvignon grapevine elements.

This paper proposes a sequential masking algorithm based on the K-means method that combines RGB and multispectral imagery for discrimination of Cabernet Sauvignon grapevine elements in unstructured natural environments, without placing any screen behind the canopy and without any previous preparation of the vineyard. In this way, image pixels are classified into five clusters corresponding to leaves, stems, branches, fruit and background. A custom-made sensory rig that integrates a CCD camera and a servo-controlled filter wheel has been specially designed and manufactured for the acquisition of images during the experimental stage. The proposed algorithm is extremely simple, efficient, and provides a satisfactory rate of classification success. All these features turn out the proposed algorithm into an appropriate candidate to be employed in numerous tasks of the precision viticulture, such as yield estimation, water and nutrients needs estimation, spraying and harvesting.

An automatic critical care urine meter.

Nowadays patients admitted to critical care units have most of their physiological parameters measured automatically by sophisticated commercial monitoring devices. More often than not, these devices supervise whether the values of the parameters they measure lie within a pre-established range, and issue warning of deviations from this range by triggering alarms. The automation of measuring and supervising tasks not only discharges the healthcare staff of a considerable workload but also avoids human errors in these repetitive and monotonous tasks. Arguably, the most relevant physiological parameter that is still measured and supervised manually by critical care unit staff is urine output (UO). In this paper we present a patent-pending device that provides continuous and accurate measurements of patient's UO. The device uses capacitive sensors to take continuous measurements of the height of the column of liquid accumulated in two chambers that make up a plastic container. The first chamber, where the urine inputs, has a small volume. Once it has been filled it overflows into a second bigger chamber. The first chamber provides accurate UO measures of patients whose UO has to be closely supervised, while the second one avoids the need for frequent interventions by the nursing staff to empty the container.

A device for automatically measuring and supervising the critical care patient's urine output.

Critical care units are equipped with commercial monitoring devices capable of sensing patients' physiological parameters and supervising the achievement of the established therapeutic goals. This avoids human errors in this task and considerably decreases the workload of the healthcare staff. However, at present there still is a very relevant physiological parameter that is measured and supervised manually by the critical care units' healthcare staff: urine output. This paper presents a patent-pending device capable of automatically recording and supervising the urine output of a critical care patient. A high precision scale is used to measure the weight of a commercial urine meter. On the scale's pan there is a support frame made up of Bosch profiles that isolates the scale from force transmission from the patient's bed, and guarantees that the urine flows properly through the urine meter input tube. The scale's readings are sent to a PC via Bluetooth where an application supervises the achievement of the therapeutic goals. The device is currently undergoing tests at a research unit associated with the University Hospital of Getafe in Spain.