Abstract Currently, the increasing interest in the study of Polylactic acid (PLA) polymer has been motivated by the potential of such material for consumer and biomedical applications. PLA is a thermoplastic polymer, biodegradable, compostable and deriving from renewable natural sources as starch and sugar. Injection molding is the most widely used process for thermoplastic micro-featured parts for to its capacity to manufacture low-cost and high repeatable micro-parts. The use of PLA for injection molded micro components is still not well stabilized due to the slow crystallization kinetics, not suitable for high performance applications. In this work, preliminary experimental studies have been performed to analyze the filling ability of PLA in a meso and a micro parts using different molding conditions to evaluate process parameters influence. The experiments results are discussed in the paper and show that injection molding proved to be suitable for meso-micro PLA product manufacturing.

Abstract Low cost marker-less motion capture (Mocap) systems can be considered an interesting technology for the objective assessment of rehabilitation processes. In particular, this paper presents a feasibility study to introduce a Mocap system as a tool to assess shoulder rehabilitation. The movements of a shoulder are complex and challenging to be captured with a marker-less system because the skeleton avatar usually oversimplifies shoulder articulation with a single virtual joint. The designed solution integrates a low-cost Mocap system with image processing techniques and convolutional neural networks to automatically detect and measure potential compensatory movements executed during an abduction, which is one of the first post-surgery exercises for shoulder rehabilitation. First, we introduce the main steps of a reference roadmap that guided the development of the Mocap solution for rehab assessment of injured shoulder. Then, the acquisition of medical knowledge is presented as well as the new Mocap solution based on the integration of convolutional neural networks and 2D motion tracking techniques. Finally, the application which automatically evaluates abductions and makes available the measurements of the scapular elevations is described. Preliminary study and future works are also presented and discussed.

Abstract In the last years, the advent of innovative technologies for tracking human motions is increasing the interest of physicians and physiotherapist, who would like to introduce new instruments for a more objective assessment of the rehabilitation processes. At present, many motion tracking systems have been developed and their ease of use and low-cost may represent the key aspects for which these systems could be really adopted both in rehabilitation centers and in rehabilitation programs at home. Several research studies confirmed the importance of continuing rehabilitation programs at home with the aim to maintain patients’ health condition at a suitable level for daily life activities. Physicians and physiotherapists need methods and tools, which can be simply adaptable for each type of patients’ category and type of rehabilitation according to the assessed pathology. For achieving this need, the technology has to be suitable for both the patient side and medical personnel side. The most suitable technology for the patients are motion tracking devices which can be used through traditional IT, such as laptops, smartphones and tablets. Also for medical personnel the ease of use is very important, physicians would like to check the patient’s rehab exercises according to their medical knowledge by exploiting daily life technology. This research work investigates on which are the best user-friendly programming tools and low-cost technology for 3D hand and finger tracking for the development of a serious game for rehabilitation exercises. The tasks are designed according to physiotherapists’ recommendations, in order to be customizable for any single user. The following sections will describe the method, the tools adopted, and the application developed.

Abstract There is great potential for using 3D printed designs fabricated via additive manufacturing processes for diverse biomedical applications. 3D printing offers capabilities for customizing designs for each new fabrication that could leverage automated design processes for personalized patient care, but there are challenges in developing accurate and efficient assessment methods. Here, we conduct a sensitivity analysis for a biological growth simulation for evaluating 3D printed lattices for regenerating bone and then use these simulations to identify performance trends. Four design topologies were compared by generating varied unit cells. Biological growth was modeled in a voxel environment by simulating the advancement of a tissue front by calculating its local curvature. Designs were generated with properties suitable for bone tissue engineering, namely 50% porosity and microscale pores. The sensitivity analysis determined trade-offs between prediction consistency and computation time, suggesting calculating curvature within a radius of 7.5 voxels is sufficient for most cases. Topologies were compared in bulk with design variations. All topologies had similar tissue growth rates for a given surface-volume ratio, but with differing unit cell sizes. These findings inform future optimization for selecting unit cells based on volume requirements and other criteria, such as mechanical stiffness. A fitted analytical relationship predicted tissue growth rate based on a design’s surface-volume ratio, which enables design evaluation without computationally expensive simulations. Lattices were 3D printed with biocompatible materials as proof-of-concepts, demonstrating the feasibility of the approach for future computational design methods for personalized medicine.

Abstract Miniaturized air-pressure sensing devices has received increasing attention during the past few decades. Pressure sensors have been explored in various potential applications, such as industrial control, healthcare, medical testing, and environmental monitoring [1–2]. Different sensing mechanisms and designs have been used for the detection of air-pressure. Of particular importance are resonant pressure sensors based on tracking the change in resonance frequency of the device with pressure. To improve the pressure sensor sensitivity, various designs have been investigated including carbon nanotubes, microcantilever, and bridge resonators. In a recent study [3], we showed a resonant pressure sensor based on an electrothermally heated clamped-clamped straight beam (cooling effect). We showed that operating the resonator near the buckling point maximizes its sensitivity [3]. In this work, we will focus on the detection of air pressure using an electrothermally heated initially curved beam exhibiting veering among its first two symmetric vibration modes, which offers more continuity in frequency variations, and hence measurements compared to buckled beams. The presented approach shows significant advantages in term of sensitivity and wide pressure range.

Abstract Polyetheretherketone (PEEK) is a high-performance, semi-crystalline thermal polymer with medical advantages such as biocompatibility and radiolucency. PEEK has an elastic modulus comparable to that of human cortical bone, so it can effectively reduce the stress shielding effect caused by the mismatch between the mechanical properties of an implant and human bone tissue. However, PEEK is biologically inert, and its use typically relies on a variety of surface modification methods, such as surface coatings of bio-ceramic materials, enhancing the surface bioactivity, and osseointegration. Compared to thermal spray or plasma spray technologies, the cold spray is carried out at relatively low temperatures, retaining the original properties of the material. This research establishes an open-source three-dimensional printer compatible with PEEK and also develops a powder-spray module based on the cold spray technology that can coat the surfaces of PEEK printings with hydroxyapatite (HA) to improve its bioactivity. This paper discusses the best parameter selection for PEEK printing, a thermal history analysis of the printing process, and the adhesion of HA powder coated on PEEK specimens with different porosities. Finally, the PEEK implant is printed to measure its performance under a vertical load.

Abstract This study is aimed at reviewing the various literature on the robot-based rehabilitation and the associated technical issues, augmentation, utilization, and safeties. During recent years, Biorobotics and Collaborative Robots have played a remarkable role to provide fast, accurate and efficient therapy and assistance. Most of these robots are equipped with various types of devices to control the intensity, duration, and precision of the training while some feedback systems have also been used to monitor the efficiency of the process and help physicians and therapists to furnish a high quality treatment. Haptic devices, Electromyography (EMG)/Electroencephalography (EEG) sensors, virtual environment and other interactive approaches have been utilized to optimize the process and to investigate different mental as well as physiological aspects. This review paper provides a comprehensive background on the human robot interactions and their outcomes in medical settings and potential research areas in the domain.

Abstract We present the modeling, control and planning for multiple magnetic mobile microrobots actuated on a planar array of coils that generates local magnetic fields. The system is capable of actuating multiple microrobots independently. Such systems have a future in micromanufacturing and biomedical applications. The coils are modeled extensively to understand the forces generated by various coil combinations of the array, and solutions for different actuation force directions are discovered. The path planning problem is formulated as a Markov decision process that solves a policy to reach a goal from any location in the workspace. The presence of multiple robots in the workspace can interfere with their motion. Hence, the coil models are used concurrently with models of interaction force between multiple magnetic robots to plan efficient paths to reach a goal in the workspace in the presence of other robots.

Abstract People with tetraplegia have significantly reduced upper body strength capabilities. The completion of activities of daily living require people living with tetraplegia to work at or near their physical limits. Improvements to the design of ‘workspaces’ and assistive devices can allow people with tetraplegia to live with increased independence. In order to make effective improvements to devices used by people with tetraplegia their strength capabilities must first be well understood. Each year there are approximately 10,400 new cases of people with tetraplegia in the US alone [1]. The purpose of this paper is to present an improved methodology for establishing multidirectional arm strength data for people with tetraplegia while in the seated position. A test rig has been designed that is a step forward in acquiring isometric upper body strength data. The test rig incorporates two three-axis load cells that allow isometric force to be measured rapidly in all directions. Using this test rig force can be measured for a full 360° rotation. Isometric strength can be measured for each arm over a 1.3m by 1.5m grid of points parallel to the sagittal plane using 100mm increments. Before the test rig used in this study was developed there was no practical way to obtain multidirectional upper body strength data in a reasonable amount of time. A preliminary study has been completed using two able-bodied subjects and one subject with C6 tetraplegia. Results of this study confirm that this methodology can be used to characterize multidirectional upper body strength. A better understanding of the strength characteristics of all people working in a seated position can enable improvements to the design of such spaces. The results highlight the dramatic reduction in the range of motion and strength capabilities for a person with tetraplegia when compared to able-bodied subjects. In particular, the preliminary results show how a cervical spinal cord injury effects what directions voluntary force can be applied over a person’s range of motion. For a number of positions force can only be effectively applied in one direction. Analysis of retested points showed no indication of fatigue effecting results. Future testing using the methodology established in this paper will be useful to provide greater insights into the strength capabilities of people with tetraplegia. The aim is to produce characteristic strength profiles for spinal cord injuries between C5 and C7. Such strength profiles will be of interest to designers of assistive devices and medical professionals. For designers, the strength information will enable changes to be made to the designs of ‘workspaces’ and assistive devices to help improve the independence of people with tetraplegia. For medical professionals this information will enable the benefits of surgical procedures such as tendon and nerve transfers to be evaluated quantitatively. This will enable people with tetraplegia to make more informed decisions when investigating possible rehabilitative surgeries.

Abstract During recent years, soft robotic is a new sub-class of the robots. Soft robotic has several engaging features, such as lightweight, low cost, simple fabrication, easy control, etc. Commercial products such as soft grippers are now available to apply in various fields and applications, for example, agriculture, medicine, machinery, etc. This paper proposes a novel method of grasping in soft robotic fields using computer vision to find the shape, size, and angle of the object to define the best type of grasping mode. Random Sample Consensus (RANSAC) was used to iteratively select randomly sampled 3D points to determine the working plane and identify the randomly placed object. Furthermore, we designed and fabricated a 3D-printed pneumatic soft actuator. The ratio of payload over weight is around 16. Experiments showed the proposed computer vision techniques and pneumatic soft gripper are capable of automatically recognize the object shape and perform soft gripping.

Abstract The Comet Assay is a well-known procedure employed to investigate the DNA damage and can be applied to several research areas such as environmental, medical and health sciences. User dependency and computation time effort represent some of the major drawbacks of the Comet Assay. Starting from this motivation, we applied a Machine Learning (ML) tool for discriminating DNA damage using a standard hand-crafted feature set. The experimental results demonstrate how the ML tool is able to objectively replicate human experts scoring (accuracy detection up to 92%) by solving the related binary task (i.e., controls vs damaged comets).

Abstract Intensive medical attention of preterm babies is crucial to avoid short-term and long-term complications. Within neonatal intensive care units (NICUs), cribs are equipped with electronic devices aimed at: monitoring, administering drugs and supporting clinician in making diagnosis and offer treatments. To manage this huge data flux, a cloud-based healthcare infrastructure that allows data collection from different devices (i.e., patient monitors, bilirubinometers, and transcutaneous bilirubinometers), storage, processing and transferring will be presented. Communication protocols were designed to enable the communication and data transfer between the three different devices and a unique database and an easy to use graphical user interface (GUI) was implemented. The infrastructure is currently used in the “Women’s and Children’s Hospital G.Salesi” in Ancona (Italy), supporting clinicians and health opertators in their daily activities.

This paper describes the design and implementation of an exoskeleton glove for infants of ages ranging from 12 months to 3 years. The glove is capable of assisting the patient in achieving a pincer grasp in active and passive modes of operation. It can record information about the hand movement, forces exerted by the fingers on the exoskeleton frame, and provide vibration stimuli to the finger tips. The data recorded by the glove can be used in early diagnosis of cerebral palsy among high risk infants. It can also be used as a standalone device for rehabilitation purposes. The hardware, software architecture and experimental validation of the system are outlined in this paper.

Advances in 3D printing are enabling new rapid prototyping strategies for complex structures, such as mechanically efficient tissue scaffolds. Here, we have developed an integrated methodology with Design, Build, and Test phases to characterize beam-based lattices for bone tissue engineering. Lattices were designed with 50% and 70% porosity with beam diameters of 0.4mm to 1.0mm fabricated with polyjet printing. Build accuracy was validated with microscopy that demonstrated overall lattice dimensions were at most 0.2mm different from design and beam diameters were at most 0.15mm different. Quasi-static compression testing showed lattice elastic moduli ranged from 28MPa to 180MPa and decreased with higher lattice porosity but increased with larger beam diameter sizes. Scaffold cages for vertebral bone fusion were prototyped using 50% and 70% porous lattices with 0.8mm diameter beams with added central voids for improved nutrient transport, reinforced shells for increased mechanics, or both. Cage stiffnesses ranged from 1.7kN/mm to 7.2kN/mm and suggests the strongest cage prototypes are suitable for carrying typical spinal loads of up to 1.65kN. The study demonstrates the value in using integrated rapid prototyping approaches for characterizing complex structures and designing novel biomedical devices.

This study aims to provide a systematic framework to apply emulation tools that could help designers to experience an extraordinary user perspective (users with some form of physical or cognitive impairment). Past studies have supported the impact of using tools that emulate a physically restricted scenario to evoke creativity and empathy among designers. The proposed approach for Empathic Experience Design (EED) guides designers to have better leverage emulation tools to understand the latent design needs from recommended extraordinary user perspectives. The framework combines the physical parameters involved while interacting with a product with the interaction activities associated with the product. This combination is used to select empathy tools that will provide an interactive experience by eliminating those parameters. By eliminating the identified parameters, participants tend to look at the design needs from the emulated extraordinary user perspectives. The framework was tested with a pilot study in which 37 participants (20 participants for Treatment Group 1 and 17 participants for Treatment Group 2) of ages 20–26 were asked to redesign a medical syringe. The extraordinary use cases implemented in this study are visual impairment, hearing impairment, low dexterity and single hand usage. The study not only tested the recommended systematic approach, but it also showed the application of an extraordinary user perspective to understand the general latent needs associated with medical devices that are less likely to be used by extraordinary users. The results are promising evidence that a simple systematic approach to implement empathic design tools could have a higher impact than an unguided instinct based approach to choose the tools. The results also show that, when applied efficiently, the approach could capture a wide variety of latent needs from potential extraordinary user perspectives’.

3D virtual reconstruction of human body parts is nowadays a common practice in many research fields such as the medical one, the manufacturing of customized products or the creation of personal avatar for gaming purpose. The acquisition can be performed with the use of an active stereo system (i.e., laser scanner, structured light sensors) or with the use of a passive image-based approach. While the former represents a consolidated approach in human modeling, the second is still an active research field. Usually, the reconstruction of a body part through a scanning system is expensive and requests to project light on the patient’s body. On the other hand, the image-based approach could use multi-photo technique to reconstruct a real scene and provides some advantages: low equipment costs (only one camera) and rapid acquisition process of the photo set. In this work, the use of the photogrammetry approach for the reconstruction of humans’ face has been investigated as an alternative to active scanning systems. Two different photogrammetric approaches have been tested to verify their potentiality and their sensitivity to configuration parameters. An initial comparison among them has been performed, considering the overall number of points detected (sparse point cloud reconstruction, dense point cloud reconstruction). Besides, to evaluate the accuracy of the reconstruction, a set of measures used in the design of wearable head-related products has been assessed.

Total hip arthroplasty (THA) is an increasingly common procedure that replaces all or part of the hip joint. The average age of patients is decreasing, which in turn increases the need for more durable implants. Revisions in hip implants are frequently caused by three primary issues: femoral loading, poor fixation, and stress shielding. First, as the age of hip implant patients decreases, the hip implants are seeing increased loading, beyond what they were traditionally designed for. Second, traditional implants may have roughened surfaces but are not fully porous which would allow bone to grow in and through the implant. Third, traditional implants are too stiff, causing more load to be carried by the implant and shielding the bone from stress. Ultimately this stress shielding leads to bone resorption and implant loosening. Additive manufacturing (AM) presents a unique opportunity for enhanced performance by allowing for personalized medicine and increased functionality through geometrically complex parts. Much research has been devoted to how AM can be used to improve surgical implants through lattice structures. To date, the authors have found no studies that have performed a complete 3D lattice structure optimization in patient specific anatomy. This paper discusses the general design of an AM hip implant that is personalized for patient specific anatomy and proposes a workflow for optimizing a lattice structure within the implant. Using this design workflow, several lattice structured AM hip implants of various unit cell types are optimized. A solid hip implant is compared against the optimized hip implants. It appears the AM hip implant with a tetra lattice outperforms the other implant by reducing stiffness and allowing for greater bone ingrowth. Ultimately it was found that AM software still has many limitations associated with attempting complex optimizations with multiple materials in patient specific anatomy. Though software limitations prevented a full 3D optimization in patient specific anatomy, the challenges associated such an approach and limitations of the current software are discussed.

A number of pathologies impact on the way a patient can either move or control the movements of the body. Traumas, articulation arthritis or generic orthopedic disease affect the way a person can walk or perform everyday movements; brain or spine issues can lead to a complete or partial impairment, affecting both muscular response and sensitivity. Each of these disorder shares the need of assessing patient’s condition while doing specific tests and exercises or accomplishing everyday life tasks. Moreover, also high-level sport activity may be worth using digital tools to acquire physical performances to be improved. The assessment can be done for several purpose, such as creating a custom physical rehabilitation plan, monitoring improvements or worsening over time, correcting wrong postures or bad habits and, in the sportive domain to optimize effectiveness of gestures or related energy consumption. The paper shows the use of low-cost motion capture techniques to acquire human motion, the transfer of motion data to a digital human model and the extraction of desired information according to each specific medical or sportive purpose. We adopted the well-known and widespread Mocap technology implemented by Microsoft Kinect devices and we used iPisoft tools to perform acquisition and the preliminary data elaboration on the virtual skeleton of the patient. The focus of the paper is on the working method that can be generalized to be adopted in any medical, rehabilitative or sportive condition in which the analysis of the motion is crucial. The acquisition scene can be optimized in terms of size and shape of the working volume and in the number and positioning of sensors. However, the most important and decisive phase consist in the knowledge acquisition and management. For each application and even for each single exercise or tasks a set of evaluation rules and thresholds must be extracted from literature or, more often, directly form experienced personnel. This operation is generally time consuming and require further iterations to be refined, but it is the core to generate an effective metric and to correctly assess patients and athletes performances. Once rules are defined, proper algorithms are defined and implemented to automatically extract only the relevant data in specific time frames to calculate performance indexes. At last, a report is generated according to final user requests and skills.

Titanium and its alloys are a class of metallic materials having high strength to weight ratio with excellent properties of resistance to temperature, corrosion and oxidation. These properties increase their use in aerospace, chemical and biomedical industries. Electrical discharge machining (EDM), a non-conventional machining process, is the most suitable process for the machining of titanium and its alloys. Generally, tool electrode for EDM application is prepared through various conventional and non-conventional machining processes. The cost of production of EDM electrodes accounts for more than 50% of the cost of the final product. Therefore, additive manufacturing (AM) technology can be suitably applied for direct manufacturing of the complex EDM electrodes. Selective laser sintering (SLS) is one of the appropriate AM processes for preparation of EDM tool electrode. In the present work, machining performance of the AlSi10Mg tool electrode produced through AM process along with copper and brass tool electrodes have been studied considering titanium alloy (Ti6Al4V) as work piece material and commercial grade EDM 30 oil as dielectric fluid. In addition to the tool electrodes, two more EDM parameters such as pulse-on-time (T on ) and discharge current (I p ) have been considered. Four performance measures like material removal rate (MRR), tool wear rate (TWR), average surface roughness (R a ) and surface crack density (SCD) are used to assess the machining performance. In order to reduce the number of experiments, design of experiment (DOE) approach like Taguchi’s L 9 orthogonal array is used. Since the performance measures are conflicting in nature, grey relational analysis (GRA) is used to convert four performance measures into an equivalent single performance measure. The best parametric condition is reported for optimal grey relational grade.

Earlier diagnosis plays a pivotal role in clinical applications, since it can strongly reduce the incidence and impact of many diseases and, consequently, the reduction of health care costs. This last aspect depends strongly from right therapy prescriptions, especially when there are various opportunities. Within this context, Clinical Decision Support Systems (CDSS) could bring several benefits. In this paper, we propose a CDSS with the aim of improving the clinician practice based on recommendations, assessment of the patient and screening of patients with risk factors to prevent chronic venous insufficiency (CVI) complications. The proposed CDSS is implemented in the Nu.Sa. cloud system, which involves thousands of italian General Practitioners (GPs) collecting data (EHR data, personal data, patient’s medical history) from millions of patients. The proposed architecture is designed to collect data from a distributed scenario where GPs are collecting clinical history and pharmacy or second level hospitals gather data from medical devices connected to the cloud over a standard data architecture. We show that exploiting the integration of the medical device VenoScreen Plus with the patient EHR, this CDSS is capable to improve preventive care, to enhance clinical performance, to influence clinical decision making and to significantly improve the decision quality levering on data driven approach.