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In manufacturing, ergonomic and productivity benefits may result from combining the sensing and dexterity of the human workers with the strength of collaborative robots (cobots). Anyway, manual tasks requiring repetitive motion or working with robots can cause musculoskeletal disorders especially of the hands. In such a context, this paper proposes a novel solution that includes both a full body inertial system and a dedicated solution for hand tracking. This allows implementing the standard methods for assessing ergonomic indexes and to introduce new advanced task analyses based on gesture evaluation. The benefits reached by the integrated system for body and hand tracking can be exploited in the virtual prototyping of collaborative workstation in the manufacturing domain. Different software packages have been considered to model and simulate the collaboration between the operator and the cobot. In particular, Unity and ROS are used to develop the virtual scene and control the cobot behavior and the HTC Vive Head Mounted Display (HMD) to interact with the virtual environment. Physical ergonomics is evaluated by using both a full body suit (XSENS) and sensorized gloves (MANUS). The solution has been applied to the simulation of a virtual production line where the operator collaborates with a six-axis cobot (NIRYO ONE). Test tasks require the operator to move and manage different objects and tools by simulating different types of grasping. Real-time feedback about ergonomics, in terms of posture evaluation and alerts in case of critical condition, is shown to the operator as well as the automatic generation of reports for the post-process evaluation of the entire process. The results show how the use of these tools can be effective in the ergonomic evaluation of a collaborative robotic workstation which requires manual tasks.

Retrograde amnesia is a severe memory loss dramatically affecting patient’s quality of life. Traumatic brain injuries, strokes, degenerative processes or metabolic disorders are the main causes. At present, rehabilitation tries to recover patients’ memory by means of neuro-cognitive exercises guided by a physiotherapist. Unfortunately, the adherence to these rehabilitation exercises drops when patients are discharged from hospital. Furthermore, conventional rehabilitation is usually performed using standard exercises, which are not customized to each patient. The reproducibility of real environments and situations is a crucial feature to guarantee the efficacy of neuro-rehabilitation and it is defined as ecological validity. Ecological validity is important for making the exercises useful to re-learn specific information and for performing daily activities with the lowest effort. Nowadays, the traditional rehabilitation for retrograde amnesia is based on a set of pictures shown to the patient to remember or learn familiar environments, such as his/her home. This approach is very limiting because the patient can see few points of view of the home without learning and memorizing how to move and get into a specific room. Therefore, the traditional approach has a low ecological validity. The advent of innovative technology, like 3D scanners and virtual reality, permit the design of innovative solutions that virtually replicate patient’s home. This research work presents a novel procedure to design serious games for neuro-cognitive rehabilitation for patient with retrograde amnesia. The proposed procedure exploits low-cost and free technologies; in particular, the Occipital Structure sensor has been chosen as 3D scanner to acquire the 3D indoor environments, which are used inside Unity to develop the game logic of the serious games. The HTC Vive Pro head mounted display has been used to interact with the serious games in an immersive way. The designed procedure makes available a set of Unity scripts to develop the serious game for new patients by changing only the 3D environment (i.e., patient’s house). The procedure has been tested by creating three different serious games and the total time to create them can be approximated to a working day. The obtained results have been shown to medical personnel who have evaluated the proposed approach with a high ecological validity and decided to plan future medical tests by involving patients.

This article presents a software platform to design serious games for the rehabilitation of severe memory loss by means of virtual reality (VR). In particular, the focus is on retrograde amnesia, a condition affecting patient's quality of life usually after brain stroke. Currently, the standard rehabilitation process includes showing pictures of familiar environments to help memory recover, while the proposed rehabilitation solution aims at developing patient-specific serious games for memory loss starting from 3D scanning of familiar environments. The Occipital Structure sensor and the Skanect application have been used for the virtualization of the real objects and the environment. Instead of following the traditional approach to design a video game during which the game logic is specifically developed for a virtual scene and the software code is not meant to be recombined, a modular procedure has been designed using Unity to interface the virtual objects of each acquired environment without modifying the game logic. In addition, the developed solution makes available a set of software modules for patient's monitoring and data management to automatically generate medical reports, which can be easily connected to each new serious game. A test has been performed to assess the main features of the VR platform and its usability recruiting ten testers. Medical personnel evaluated positively the platform, and they highlighted the importance of objective data to improve the ecological validity of the cognitive rehabilitation for retrograde amnesia.

In the last past years, computer-aided technologies to improve existing products by widening the design space have been largely investigated. Topology optimization and generative design are two of the most representative technologies of such kind. This paper aims at investigating the use of generative design and topology optimization techniques to improve products whose design has not changed radically over the years. The product under investigation is a disk brake floating caliper that is the most common solution for commercial vehicles. In general, increasing the stiffness of the floating caliper while keeping its weight under control is desirable both from performance and fuel consumption point of view. The solution here proposed aims at exploiting two new ways to approach the engineering design process and evaluate which one is more suitable for problems of this kind. Starting from the original carrier shape, acquired with laser scanning, the two technologies have been applied on the same initial conditions. The initial design space volume corresponds to the acquired shape, the loads and the constraints for the simulation have been drawn reasonably to resemble the actual operating conditions. Keeping the input parameters constants, two different off-the-shelf software packages have been used to perform the computation and with the objective of maximizing the stiffness of the carrier while reducing its mass. The comparison and the improvements on the final designs have been drawn taken as reference to the original caliper.

A 3D sketching system is presented for transforming an ideation to an actual CAD model using Human Computer Interaction (HCI). The system uses a Leap motion controller to capture human gestures, and translated them by a recognition model. The pinch and pull gestures are used to represent actions for flexible manipulations on control points coordinates of NURBS surfaces. The continuous motion of the designers hands is converted to morphological/geometrical and mathematical values. Both cases of single and dual hands are developed, offering the designer a variety of resolution tools to convey their ideas and creativity.

Marker-less motion capture (MOCAP) systems based on consumer technology simplify the analysis of movements in several research fields such as industry, healthcare and sports. Even if the marker-less MOCAP systems have performances with precision and accuracy lower than the marker-based MOCAP solutions, their low cost and ease of use make them the most suitable tools for full-body movements analysis. The most interesting category is relative to the use of RGB-D devices. This research work aims to compare the performances of the last two generations of Kinect devices as marker-less MOCAP systems: Microsoft Kinect v2 and Azure devices. To conduct the tests, a list of specific movements is acquired and evaluated. This work measures the improvements of the Azure in tracking human body movements. The gathered results are presented and discussed by evaluating performances and limitations of both marker-less MOCAP systems. Conclusions and future developments are shown and discussed.

In recent years, the use and demand of bicycles have increased thanks to the growing attention to the environment and due to the COVID-19 pandemic situation. At the same time, the design of the bicycles has remained substantially unchanged, improving in materials and components technology. In the off-road sector, two diametrically opposed categories have emerged in terms of comfort and pedalling efficiency. The goal of this research is to introduce a first methodological approach for the optimization of a mountain bike frame. The behaviour of the developed frame aims to combine the pedalling benefits now available only in different and non-comparable bicycle configurations. The first step concerns the modelling of a generic off-road bicycle frame, then its behaviour has been simulated for specific load cases. Subsequently, the part of the bicycle that best performed the double function of compliance and rigidity has been sought through an analysis of the strain energy using FE simulations. Hence, the reference region has been topologically optimized to provide adequate chassis travel performance. The analysis scheme has been iteratively repeated also on other parts of the frame until an acceptable solution is obtained for the utilize presented. The final configuration permits a rear tube and bottom bracket displacement of 10.4 mm and 2.4 mm compared to the 0.5 mm and 0.4 mm of the original frame respectively. The approach described can be proposed as a support for the search for an innovative design for products with unchanged geometries due to the inertia of the designers. At the same time, this methodology aims to expand the possible use of topological optimization, moving away from the classic constraint schemes present in various software.

The rehabilitation process after stroke may exhibit some limits regarding physical therapy adherence and there could be a lack of patients’ motivation and trust impacting on the quality of the rehabilitation procedure. This research work aims at introducing a specific interactive design method to develop rehabilitation tools based on the medical knowledge and VR devices to recover motor skills of patients’ hands after stroke and to increase the patients’ adherence. The method we propose consists of three main steps: medical requirement analysis, identification of ICT tools, and medical data management. A case study related to hand rehabilitation is also presented.

In the last years, the advent of low-cost markerless motion capture systems fostered their use in several research fields, such as healthcare and sport. Any system presents benefits and drawbacks that have to be considered to design a Mocap solution providing a proper motion acquisition for a specific context. In order to evaluate low-cost technology, this research work focuses on the evaluation of the accuracy of two categories of devices: the RGB active cameras and the RGB-D, or depth sensors devices. In particular, GoPro Hero 6 active cameras and Microsoft Kinect v2 devices have been selected as representative of the two categories. In particular, this work evaluates and compares the performances of the two systems used to track the position of human articulations. The two devices have been chosen among those available on the market after a state of the art has been completed. Before starting with the campaign of acquisition, the number of sensors and their layout have been designed to optimize the acquisition with both mark-less Mocap systems. Their comparison is based on a list of specific movements of upper and lower limbs. Each movement has been acquired simultaneously, to guarantee the same test conditions. The results have been organized, compared and discussed by evaluating performances and limitations of both solutions related to specific context of use. Conclusions highlight the best candidate technology.

In physical rehabilitation, motion capture solutions are well-known but not as widespread as they could be. The main limit to their diffusion is not related to cost or usability but to the fact that the data generated when tracking a person must be elaborated according to the specific context and aim. This paper proposes a solution including customized motion capture and data elaboration with the aim of supporting medical personnel in the assessment of spinal cord-injured (SCI) patients using a wheelchair. The configuration of the full-body motion capturing system is based on an asymmetric 3 Microsoft Kinect v2 sensor layout that provides a path of up to 6 m, which is required to properly track the wheelchair. Data elaboration is focused on the automatic recognition of the pushing cycles and on plotting any kinematic parameter that may be interesting in the assessment. Five movements have been considered to evaluate the wheelchair propulsion: the humeral elevation, the horizontal abduction of the humerus, the humeral rotation, the elbow flexion and the trunk extension along the sagittal plane. More than 60 volunteers with a spinal cord injury were enrolled for testing the solution. To evaluate the reliability of the data computed with SCI APPlication (APP) for the pushing cycle analysis, the patients were subdivided in four groups according to the level of the spinal cord injury (i.e., high paraplegia, low paraplegia, C7 tetraplegia and C6 tetraplegia). For each group, the average value and the standard deviation were computed and a comparison with similar acquisitions performed with a high-end solution is shown. The measurements computed by the SCI-APP show a good reliability for analyzing the movements of SCI patients&rsquo, propulsion wheelchair.

Total Knee Arthroplasty is one of the most commonly performed orthopedic procedures and it is expected to grow in the next future. In the last past years, computer-assisted procedures represent one of the trends that are transforming the way of practicing medicine. Cornering the Total Knee Arthroplasty, digital models of the joints have been used to carry out simulation of their kinematics and mechanical performance. Whilst for the 3D digital reconstruction of the patient geometry several studies have been conducted, an approximated geometry of the prosthesis has been several times employed, with undeniable consequences on the final results. This paper aims at comparing two non-contact reverse engineering technologies to acquire the shape of femoral components employed for total knee arthroplasty. A high-level device (Konika Minolta Vivid 9i) and a mid-low cost laser (NextEngine) has been compared. For the comparison, a systematic procedure of acquisition and elaboration of the results has been adopted in order to have as unbiased as possible results. The procedure involves the use of the proprietary software of the scanners for the elaboration of the raw data and the meshing procedure has been kept the same for all the models. Since the as-is acquired mesh is of high-resolution, a decimation procedure has been carried out in order to make the 3D models lighter and easier to be handled. Once the decimation procedure has been evaluated comparing the original and the simplified models to one another, the digitalized models have been compared with the measurements taken from a coordinate measuring machines. As a preliminary result, the two lasers seem to be adequate to accomplish the reverse engineering process as required by this application. Of course, the mid-low cost laser would be preferable whether the performance will be confirmed to be (statistically) equal.

Motion capture (Mocap) is applied to motor rehabilitation of patients recovering from a trauma, a surgery, or other impairing conditions. Some rehabilitation exercises are easily tracked with low-cost technologies and a simple Mocap setup, while some others are extremely hard to track because they imply small movements and require high accuracy. In these last cases, the obvious solution is to use high performing motion tracking systems, but these devices are generally too expensive in the rehabilitation context. The aim of this paper is to provide a Mocap solution suitable for any kind of exercise but still based on low-cost sensors. This result can be reached embedding some artificial intelligence (AI), in particular a convolutional neural network (CNN), to gather a better outcome from the optical acquisition. The paper provides a methodology including the way to perform patient's tracking and to elaborate the data from infra-red sensors and from the red, green, blue (RGB) cameras in order to create a user-friendly application for physiotherapists. The approach has been tested with a known complex case concerning the rehabilitation of shoulders. The proposed solution succeeded in detecting small movements and incorrect patient behavior, as for instance, a compensatory elevation of the scapula during the lateral abduction of the arm. The approach evaluated by medical personnel provided good results and encouraged its application in different kinds of rehabilitation practices as well as in different fields where low-cost Mocap could be introduced.

Background and Objective The paper presents a novel procedure based on 3D scanning and 3D modelling to automatically assess linear and volumetric measurements of an arm and to be further applied to patients affected by post breast cancer lymphedema. The aim is the creation of a virtual platform easily usable by medical personnel to get more objective evaluations during the lymphedema treatment. Methods The procedure is based on the 3D scanning of the arm using the Occipital Structure Sensor and an ad-hoc developed application, named Lym 3DLab. Lym 3DLab emulates the traditional measurement methods, which consist in taking manual circumference measurements or using the water displacement method. These measurements are also used to design the compression stockings, the typical orthopaedic device used for lymphedema treatment. A validation test has been performed to compare the measurements computed by Lym 3DLab with both water displacement and manual circumference measurements. Eight volunteers have been involved who are not affected by lymphedema. Furthermore, a specific usability test has been performed to evaluate the 3D scanning procedure by involving four physiotherapists. Results The comparison between the volumes has highlighted how all the 3D acquired models have their volumes inside a range of acceptability. This range has been defined by considering the sensitivity error of the tape measure used to measure the water displacement. The comparison between the perimeters of cross sections computed with Lym 3DLab and the circumference measurements has shown results that are very accurate with an average difference of 2 mm. The measure errors have been considered negligible by the medical personnel who have evaluated the proposed procedure more accurate than the traditional ones. The test with physiotherapists has shown a high level of usability of the whole virtual environment, but the 3D scanning procedure requires an appropriate training of the personnel to make the 3D acquisition as fast and efficient as possible. Conclusions The achieved results and the physiotherapists’ feedback allow planning a future test with patients affected by lymphedema in collaboration with the hospital. A further test has been planned to use the computed measurements to design orthopaedic compression stockings.

This chapter presents an overview of the virtual humans/digital human models (DHMs) that can be considered along the design and manufacturing processes. It first introduces a brief historical description, as well as the main problems to be faced and the potential of such models. Then, the chapter presents a taxonomy that subdivides DHMs into five main categories, highlighting the different levels of human model details and their applications. The integration of DHMs with virtual/augmented reality technology and motion capture systems is also considered respectively to improve the level of interaction and realism within the virtual environment and to drive the virtual human and facilitate the evaluation of comfort and prediction of injuries that could rise when executing a task. The chapter also describes applicative examples of each type of DHM for both design and manufacturing.

This research work presents a preliminary study for the assessment of lymphedema using low-cost 3D scanning and modelling technology. The aim is to develop a methodology to measure the anatomical key features of the upper limbs lymphedema using a 3D scanning technology and an ad-hoc developed application, named Lym 3DLab. The application is able to automatically measure both perimeters of cross sections and volumes of arm segments for medical evaluation and design of compression stockings using the upper limb polygonal mesh. The scanning procedure is based on a Microsoft Kinect v1 as scanner and the low-cost Skanect tool, which creates the polygonal mesh of the 3D acquisition. Lym 3DLab has been developed using open-source Software Development Kits, such as Qt and Visualization Toolkit. The acquired volumes have been compared with the water displacement method, which is considered the gold standard for measuring volumes of limbs affected by lymphedema. A preliminary test has been performed to compare volumes measured using the developed procedure with the gold standard. Five volunteers have been involved who are not affected by lymphedema. The arm volume measured with water displacement have been compared with the volume computed using 3D model of arm in Lym 3DLab. The range of differences is between −6,75 cm3 and 9,40 cm3. Reached results are the base for planning further test with a large number of patients affected by lymphedema in collaboration with a hospital.

This paper presents an approach for monitoring exercises of hand rehabilitation for post stroke patients. The developed solution uses a leap motion controller as hand-tracking device and embeds a supervised machine learning. The K-nearest neighbor methodology is adopted for automatically characterizing the physiotherapist or helper hand movement resulting a unique movement pattern that constitutes the basis of the rehabilitation process. In the second stage, an evaluation of the patients rehabilitation exercises results is compared to the movement pattern of the patient and results are presented, saved and statistically analyzed. Physicians and physiotherapists monitor and assess patients’ rehabilitation improvements through a web application, furthermore, offer medical assisted rehabilitation processes through low cost technology, which can be easily exploited at home. Recorded tracked motion data and results can be used for further medical study and evaluating rehabilitation trends according to patient’s rehabilitation practice and improvement.

The research work presents a preliminary study to create a virtual reality platform for the medical assessment of spatial extrapersonal neglect, a syndrome affecting human awareness of a hemi-space that may be caused by cerebral lesions. Nowadays, the extrapersonal neglect is assessed by using real objects positioned in the space around the patient, with a poor capability of repetition and data gathering. Therefore, the aim of this research work is the introduction of a virtual reality solution based on consumer technology for the assessment of the extrapersonal neglect. By starting from the needs of the involved medical personnel, an online serious-game platform has been developed, which permits to perform a test and a real-time evaluation by means of objective data tracked by exploited technologies, i.e. an HTC Vive Pro head mounted display and ad-hoc IT solutions. The test is based on a virtual environment composed by a table on which twenty objects have been placed, ten on the right side and ten on the left side. The whole 3D virtual environment has been developed using low-cost and free development tools, such as Unity and Blender. The interaction with the virtual environment is based on voice recognition technology, therefore the patient interact with the application by pronouncing the name of each object aloud. The VR application has been developed according to an online gaming software architecture, which permits to share the 3D scene by exploiting a Wi-Fi hotspot network. Furthermore, the on-line gaming software architecture allows sending and receiving data between the doctor’s laptop and the VR system used by the patient on another laptop. The therapist can see through his/her personal computer a real time faithful replica of the test performed by the patient in order to have a fast feedback on patient’s field of view orientation during the evaluation of 3D objects. A preliminary test has been carried out to evaluate the ease of use for medical personnel of the developed VR platform. The big amount of recorded data and the possibility to manage the selection of objects when the voice commands are not correctly interpreted has been greatly appreciated. The review of the performed test represents for doctors the possibility of objectively reconstructing the improvements of patients during the whole period of the rehabilitation process. Medical feedback highlighted how the developed prototype can already be tested involving patients and thus, a procedure for enrolling a group of patients has been planned. Finally, future tests have been planned to compare the developed solution with the Caterine Bergero Scale to define a future standardization.

The effectiveness of custom-made prostheses or orthoses heavily depends on the experience and skills of the personnel involved in their production. For complex devices, such as lower limb prosthesis, a conventional manual approach affects the process at the point that the result is frequently not acceptable at the first trial. The paper presents a computer-aided environment, named socket modelling assistant $$^{2}$$ (i.e., $$\hbox {SMA}^{2})$$ , to interactively design the socket of lower limb prosthesis by implementing a set of design rules extrapolated from the traditional development process. The new computer-aided environment has been implemented embracing a low-cost philosophy and using open source libraries to provide a solution affordable also by small orthopaedic laboratories. The system permits to modify and interact with the 3D model of residual limb to create the socket geometric model ready to be manufactured by means of additive manufacturing. $$\hbox {SMA}^{2}$$ embeds medical knowledge related to the device functioning, the conventional process and the way orthopaedic technicians work so that it can be much more reliable and repeatable compared to the conventional process, but still enough similar to it to be accepted by the involved personnel. In the paper, the new 3D design procedure is described in detail, from the acquisition of patient’s data to preliminary and customized modelling, and new geometric tools to perform context–related operations are shown. A case study is used to clarify the way the system works and to provide an example of the outcome.

Nowadays, healthcare centers are not familiar with quantitative approaches for patients’ gait evaluation. There is a clear need for methods to obtain objective figures characterizing patients’ performance. Actually, there are no diffused methods for comparing the pre- and post-operative conditions of the same patient, integrating clinical information and representing a measure of the efficiency of functional recovery, especially in the short-term distance of the surgical intervention. To this aim, human motion tracking for medical analysis is creating new frontiers for potential clinical and home applications. Motion Capture (Mocap) systems are used to allow detecting and tracking human body movements, such as gait or any other gesture or posture in a specific context. In particular, low-cost portable systems can be adopted for the tracking of patients’ movements. The pipeline going from tracking the scene to the creation of performance scores and indicators has its main challenge in the data elaboration, which depends on the specific context and to the detailed performance to be evaluated. The main objective of this research is to investigate whether the evaluation of the patient’s gait through markerless optical motion capture technology can be added to clinical evaluations scores and if it is able to provide a quantitative measure of recovery in the short postoperative period. A system has been conceived, including commercial sensors and a way to elaborate data captured according to caregivers’ requirements. This allows transforming the real gait of a patient right before and/or after the surgical procedure into a set of scores of medical relevance for his/her evaluation. The technical solution developed in this research will be the base for a large acquisition and data elaboration campaign performed in collaboration with an orthopedic team of surgeons specialized in hip arthroplasty. This will also allow assessing and comparing the short run results obtained by adopting different state-of-the-art surgical approach for the hip replacement.

This work proposes a human computer interface system using a motion capture device, for assisting in CAD modeling and designing. The leap motion controller input data serves as an interactive tool which is transformed to surface representation of NURBS surfaces. Acquiring the sensor data is done by analyzing the images using a feature recognition module which in this work was updated and enhanced. Joints of hands and fingers are sufficed, and define recognized 3D image of a human hand. To use relevant information from the Leap Motion device, it is mandatory to interpret and map the input sensor data into 3D software coordinate system. This is done by implementing various transformations and a normalization procedures. Methods corresponding between these representation are developed in this work, to reduce noise thus providing accuracy. The DOF provided by the definition of the NURBS parametric surfaces and the Leap Motion Controller provide flexible design characteristics.

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.