Skeletal muscle differentiation of human iPSCs meets bioengineering strategies: perspectives and challenges

Although skeletal muscle repairs itself following small injuries, genetic diseases or severe damages may hamper its ability to do so. Induced pluripotent stem cells (iPSCs) can generate myogenic progenitors, but their use in combination with bioengineering strategies to modulate their phenotype has not been sufficiently investigated. This review highlights the potential of this combination aimed at pushing the boundaries of skeletal muscle tissue engineering. First, the overall organization and the key steps in the myogenic process occurring in vivo are described. Second, transgenic and non-transgenic approaches for the myogenic induction of human iPSCs are compared. Third, technologies to provide cells with biophysical stimuli, biomaterial cues, and biofabrication strategies are discussed in terms of recreating a biomimetic environment and thus helping to engineer a myogenic phenotype. The embryonic development process and the pro-myogenic role of the muscle-resident cell populations in co-cultures are also described, highlighting the possible clinical applications of iPSCs in the skeletal muscle tissue engineering field

An Interactive Digital-Twin Model for Virtual Reality Environments to Train in the Use of a Sensorized Upper-Limb Prosthesis

In recent years, the boost in the development of hardware and software resources for building virtual reality environments has fuelled the development of tools to support training in different disciplines. The purpose of this work is to discuss a complete methodology and the supporting algorithms to develop a virtual reality environment to train the use of a sensorized upper-limb prosthesis targeted at amputees. The environment is based on the definition of a digital twin of a virtual prosthesis, able to communicate with the sensors worn by the user and reproduce its dynamic behaviour and the interaction with virtual objects. Several training tasks are developed according to standards, including the Southampton Hand Assessment Procedure, and the usability of the entire system is evaluated, too

Reliable in vitro method for the evaluation of the primary stability and load transfer of transfemoral prostheses for osseointegrated implantation

Osseointegrated transfemoral prostheses experience aseptic complications with an incidence between 3% and 30%. The main aseptic risks are implant loosening, adverse bone remodeling, and post-operative periprosthetic fractures. Implant loosening can either be due to a lack of initial (primary) stability of the implant, which hinders bone ingrowth and therefore prevents secondary stability, or, in the long-term, to the progressive resorption of the periprosthetic bone. Post-operative periprosthetic fractures are most often caused by stress concentrations. A method to simultaneously evaluate the primary stability and the load transfer is currently missing. Furthermore, the measurement errors are seldom reported in the literature. In this study a method to reliably quantify the bone implant interaction of osseointegrated transfemoral prostheses in terms of primary stability and load transfer was developed, and its precision was quantified. Micromotions between the prosthesis and the host bone and the strains on the cortical bone were measured on five human cadaveric femurs with a typical commercial osseointegrated implant. To detect the primary stability of the implant and the load transfer, cyclic loads were applied, simulating the peak load during gait. Digital Image Correlation was used to measure displacements and bone strains simultaneously throughout the test. Permanent migrations and inducible micromotions were measured (three translations and three rotations), while, on the same specimen, the full-field strain distribution on the bone surface was measured. The repeatability tests showed that the devised method had an intra-specimen variability smaller than 6 μm for the translation, 0.02 degrees for the rotations, and smaller than 60 microstrain for the strain distribution. The inter-specimen variability was larger than the intra-specimen variability due to the natural differences between femurs. Altogether, the measurement uncertainties (intrinsic measurement errors, intra-specimen repeatability and inter-specimen variability) were smaller than critical levels of biomarkers for adverse remodelling and aseptic loosening, thus allowing to discriminate between stable and unstable implants, and to detect critical strain magnitudes in the host bone. In conclusion, this work showed that it is possible to measure the primary stability and the load transfer of an osseointegrated transfemoral prosthesis in a reliable way using a combination of mechanical testing and DIC

Quantitative analysis of interface pressures in transfemoral prosthetic sockets

Background: Among the different factors affecting socket comfort, the pressure applied on residual limb tissues is a crucial parameter for the success or failure of any prosthetic device. However, only a few incomplete data are available on people with transfemoral amputation, in this regard. This work aims at filling this gap in the literature. Methods: Ten people with transfemoral amputation wearing 3 different socket designs were recruited in this study: 2 ischial containment sockets featured by proximal trim lines that contain the ischial tuberosity and ramus and greater trochanter, 2 subischial sockets with proximal trim lines under the ischium level, and 6 quadrilateral sockets with proximal trim lines that contain the greater trochanter and create a horizontal seat for the ischial tuberosity. The pressure values at the anterior, lateral, posterior, and medial areas of the socket interface were recorded during 5 locomotion tasks (ie, horizontal, ascent, and descent walking, upstairs and downstairs) by using an F-Socket System (Tekscan Inc., Boston, MA). Gait segmentation was performed by exploiting plantar pressure, which was acquired by an additional sensor under the foot. Mean and standard deviation of minimum and maximum values were calculated for each interface area, locomotion task, and socket design. The mean pressure patterns during different locomotion tasks were reported, as well. Results: Considering all subjects irrespective of socket design, the mean pressure range resulted 45.3 (posterior)-106.7 (posterior) kPa in horizontal walking; 48.3 (posterior)-113.8 (posterior) kPa in ascent walking; 50.8 (posterior)-105.7 (posterior) kPa in descent walking; 47.9 (posterior)-102.9 (lateral) kPa during upstairs; and 41.8 (posterior)-84.5 (anterior) kPa during downstairs. Qualitative differences in socket designs have been found. Conclusions: These data allow for a comprehensive analysis of pressures acting at the tissue-socket interface in people with transfemoral amputation, thus offering essential information for the design of novel solutions or to improve existing ones, in this field

Long-Term Upper-Limb Prosthesis Myocontrol via High-Density sEMG and Incremental Learning

Noninvasive human-machine interfaces such as surface electromyography (sEMG) have long been employed for controlling robotic prostheses. However, classical controllers are limited to few degrees of freedom (DoF). More recently, machine learning methods have been proposed to learn personalized controllers from user data. While promising, they often suffer from distribution shift during long-term usage, requiring costly model re-training. Moreover, most prosthetic sEMG sensors have low spatial density, which limits accuracy and the number of controllable motions. In this work, we address both challenges by introducing a novel myoelectric prosthetic system integrating a high density-sEMG (HD-sEMG) setup and incremental learning methods to accurately control 7 motions of the Hannes prosthesis. First, we present a newly designed, compact HD-sEMG interface equipped with 64 dry electrodes positioned over the forearm. Then, we introduce an efficient incremental learning system enabling model adaptation on a stream of data. We thoroughly analyze multiple learning algorithms across 7 subjects, including one with limb absence, and 6 sessions held in different days covering an extended period of several months. The size and time span of the collected data represent a relevant contribution for studying long-term myocontrol performance. Therefore, we release the DELTA dataset together with our experimental code

A Locomotion Mode Recognition Algorithm Using Adaptive Dynamic Movement Primitives

Control systems of robotic prostheses should be designed to decode the users' intent to start, stop, or change locomotion; and to select the suitable control strategy, accordingly. This paper describes a locomotion mode recognition algorithm based on adaptive Dynamic Movement Primitive models used as locomotion templates. The models take foot-ground contact information and thigh roll angle, measured by an inertial measurement unit, for generating continuous model variables to extract features for a set of Support Vector Machines. The proposed algorithm was tested offline on data acquired from 10 intact subjects and 1 subject with transtibial amputation, in ground-level walking and stair ascending/descending activities. Following subject-specific training, results on intact subjects showed that the algorithm can classify initiatory and steady-state steps with up to 100.00% median accuracy medially at 28.45% and 27.40% of the swing phase, respectively. While the transitory steps were classified with up to 87.30% median accuracy medially at 90.54% of the swing phase. Results with data of the transtibial amputee showed that the algorithm classified initiatory, steady-state, and transitory steps with up to 92.59%, 100%, and 93.10% median accuracies medially at 19.48%, 51.47%, and 93.33% of the swing phase, respectively. The results support the feasibility of this approach in robotic prosthesis control

A Workflow for Studying the Stump-Socket Interface in Persons with Transtibial Amputation through 3D Thermographic Mapping

The design and fitting of prosthetic sockets can significantly affect the acceptance of an artificial limb by persons with lower limb amputations. Clinical fitting is typically an iterative process, which requires patients' feedback and professional assessment. When feedback is unreliable due to the patient's physical or psychological conditions, quantitative measures can support decision-making. Specifically, monitoring the skin temperature of the residual limb can provide valuable information regarding unwanted mechanical stresses and reduced vascularization, which can lead to inflammation, skin sores and ulcerations. Multiple 2D images to examine a real-life 3D limb can be cumbersome and might only offer a partial assessment of critical areas. To overcome these issues, we developed a workflow for integrating thermographic information on the 3D scan of a residual limb, with intrinsic reconstruction quality measures. Specifically, workflow allows us to calculate a 3D thermal map of the skin of the stump at rest and after walking, and summarize this information with a single 3D differential map. The workflow was tested on a person with transtibial amputation, with a reconstruction accuracy lower than 3 mm, which is adequate for socket adaptation. We expect the workflow to improve socket acceptance and patients' quality of life