Advanced systems based on bioreactors and scaffolds are an essential step towards the development of more predictive and ethical alternatives to animal experiments. Size, modularity, automation, monitoring and essential design are crucial because these elements will ease the transition from old technology and accelerate their acceptance into mainstream research. Based on these requirements, the interconnected transparent sensorised “lego†bioreactors designed in our labs have been used to generate physiologically relevant disease and toxicity models which recapitulate systemic responses impossible to observe in standard cell cultures. The disease model is an interconnected bioreactor circuit with i) adipose tissue in 3D in 3 different concentrations representing normo-weight, over weight and obese body mass indices, ii) human hepatocytes on porous collagen scaffolds and iii) monolayers of human endothelial cells. High adiposity and elevated glucose levels induce systemic and endothelial inflammation in the circuit, as observed in overweight and diabetic humans (Iori et al., 2012). Using similar technology a three-tissue circuit for monitoring the absorption, distribution, metabolism and toxicity of nanoparticles was developed in the context of the EU project InLiveTox (Ucciferri et al., 2014). The results were strikingly similar to those observed in animal experiments demonstrating that the dynamic 3D in-vitro models are ethical, meaningful and economically viable replacements.
In cardiac tissue engineering, the use of bioreactors is fundamental for applying controlled mechanical stimuli on the cells and recreate a physiological environment for cardiomyocytes cultures. This work is focused on an innovative Sensorized Squeeze PRessure (S2PR) bioreactor, able to apply a periodic contactless hydrodynamic pressures on 3D porous constructs. The fluid-dynamic environment inside the bioreactor was fully characterized using computational models, focusing on the pressures and fluid velocity profiles generated in the porous scaffold during the cyclic stimulation.
This paper presents a kinesthetic glove realized with knitted piezoresistive fabric (KPF) sensor technology. The glove forefinger area is sensorized by two KPF goniometers obtained on the same piezoresistive substrate. The piezoresistive textile is used for the realization of both electrogoniometers and connections, thus avoiding mechanical constraints due to metallic wires. Sensors are characterized in comparison with commercial goniometers. The glove behavior is pointed out in terms of methacarpal-phalangeal and interphalangeal joint movement reconstruction.
Exploiting hand kinematic synergies and wearable under-sensing for hand functional grasp recognition
Publication Type
Conference Paper
Year of Publication
2014
Conference Name
4th International Conference on Wireless Mobile Communication and Healthcare - "Transforming healthcare through innovations in mobile and wireless technologies"
Despite some prematurely optimistic claims, the ability of robots to grasp general objects in unstructured environments still remains far behind that of humans. This is not solely caused by differences in the mechanics of hands: indeed, we show that human use of a simple robot hand (the Pisa/IIT SoftHand) can afford capabilities that are comparable to natural grasping. It is through the observation of such human-directed robot hand operations that we realized how fundamental in everyday grasping and manipulation is the role of hand compliance, which is used to adapt to the shape of surrounding objects. Objects and environmental constraints are in turn used to functionally shape the hand, going beyond its nominal kinematic limits by exploiting structural softness. In this paper, we set out to study grasp planning for hands that are simple — in the sense of low number of actuated degrees of freedom (one for the Pisa/IIT SoftHand) — but are soft, i.e. continuously deformable in an infinity of possible shapes through interaction with objects. After general considerations on the change of paradigm in grasp planning that this setting brings about with respect to classical rigid multi-dof grasp planning, we present a procedure to extract grasp affordances for the Pisa/IIT SoftHand through physically accurate numerical simulations. The selected grasps are then successfully tested in an experimental scenario.
XIM-Engine: a software framework to support the development of interactive applications that uses conscious and unconscious reactions in immersive mixed reality
The development of systems that allow multimodal interpretation of human-machine interaction is crucial to advance our understanding and validation of theoretical models of user behavior. In particular, a system capable of collecting, perceiving and interpreting unconscious behavior can provide rich contextual information for an interactive system. One possible application for such a system is in the exploration of complex data through immersion, where massive amounts of data are generated every day both by humans and computer processes that digitize information at different scales and resolutions thus exceeding our processing capacity. We need tools that accelerate our understanding and generation of hypotheses over the datasets, guide our searches and prevent data overload. We describe XIM- engine, a bio-inspired software framework designed to capture and analyze multi-modal human behavior in an immersive environment. The framework allows performing studies that can advance our understanding on the use of conscious and unconscious reactions in interactive systems.
This paper presents the first step toward the study of minimum timetrajectories for a differentialdrive robot, which is equipped with a fixed and limited Field-Of-View (FOV) camera, towards a desired configuration while keeping a given landmark in sight during maneuvers. While several previous works have provided a complete synthesis of shortest paths in case of both nonholonomic and FOV constraints, to the best of our knowledge, this paper represents the first analysis of minimum timetrajectories with the two constraints. After showing the extremals of the problem at hand, i.e. straight lines, rotations on the spot, logarithmic spirals and involute of circles, we provide the optimal control laws that steer the vehicle along the path and the cost in terms of time along each extremal. Moreover, we compare some concatenations of extremals in order to reduce the complexity of the problem toward the definition of a sufficient finite set of optimal maneuvers.
The objective of the EU project INTERACTION is to develop an unobtrusive and modular sensing system for objective monitoring of daily-life motor performance of stroke survivors. This will enable clinical professionals to advise their patients about their continued daily-life activity profile and home training, and evaluate and optimize rehabilitation programs.A modular textile-integrated sensing system was developed and performance and capacity measures were proposed and clinically tested in stroke subject.Telemonitoring facilities were developed and tested. In the last stage of the project, the system will be tested during daily-life.
The objective of the INTERACTION Eu project is to develop and validate an unobtrusive and modular system for monitoring daily life activities, physical interactions with the environment and for training upper and lower extremity motor function in stroke subjects. This paper describes the development and preliminary testing of the project sensing platform made of sensing shirt, trousers, gloves and shoes. Modular prototypes were designed and built considering the minimal set of inertial, force and textile sensors that may enable an efficient monitoring of stroke patients. The single sensing elements are described and the results of their preliminary lab-level testing are reported.
One of the main challenges in the study of human be- havior is to quantitatively assess the participants? affective states by measuring their psychophysiological signals in ecologically valid conditions. The quality of the acquired data, in fact, is often poor due to artifacts generated by natural interactions such as full body movements and gestures. We created a technology to address this problem. We enhanced the eXperience Induction Machine (XIM), an immersive space we built to conduct experiments on human behavior, with unobtrusive wearable sensors that measure electrocardiogram, breathing rate and electrodermal response. We conducted an empirical validation where participants wearing these sensors were free to move in the XIM space while exposed to a series of visual stimuli taken from the International Affective Picture System (IAPS). Our main result consists in the quan- titative estimation of the arousal range of the affective stimuli through the analysis of participants? psychophysiological states. Taken together, our findings show that the XIM constitutes a novel tool to study human behavior in life-like conditions.
