Augmented visual, auditory, haptic, and multimodal feedback in motor learning: A review

It is generally accepted that augmented feedback, provided by a human expert or a technical display, effectively enhances motor learning. However, discussion of the way to most effectively provide augmented feedback has been controversial. Related studies have focused primarily on simple or artificial tasks enhanced by visual feedback. Recently, technical advances have made it possible also to investigate more complex, realistic motor tasks and to implement not only visual, but also auditory, haptic, or multimodal augmented feedback. The aim of this review is to address the potential of augmented unimodal and multimodal feedback in the framework of motor learning theories. The review addresses the reasons for the different impacts of feedback strategies within or between the visual, auditory, and haptic modalities and the challenges that need to be overcome to provide appropriate feedback in these modalities, either in isolation or in combination. Accordingly, the design criteria for successful visual, auditory, haptic, and multimodal feedback are elaborate

Design and implementation of a compact high-throughput echelle spectrometer using off-the-shelf off-axis parabolic mirrors for analysis of biological samples by LIBS (Conference Presentation)

This work presents the development of an Echelle spectrometer that is optimized for the characterization of laser-driven plasma emission of biological samples for application in smart laser surgery systems. Despite the compact (portable) and cost-efficient design of the developed spectrometer, it allows analyzing the spectrum of a plasma emitted from bone, and its surrounding soft tissues (bone marrow, muscle, and fat) in nearly the same way as a full-sized Echelle spectrometer as used in commercial laser-induced breakdown spectroscopy (LIBS) systems. Most of the commercially available Echelle spectrometers on the market use a long focal length on-axis mirror to have a reasonable F number (which defines the optical throughput of the system) and low aberration. While a long focal length requires less tilting of the mirror than a shorter focal length (the higher the tilt angle, the higher the aberration), a long focal length increases the system size and decreases sensitivity (i.e., less optical throughput). In this work, a parabolic 90o off-axis mirror with a focal length of 152.4 mm and a diameter of 50.8 mm, which leads to an F-number of 3, has been used. This low F-number provides a high optical throughput compared to other similar commercial Echelle spectrometers with F-numbers of 10 or more [1-5]. Since most of the important peaks in biological tissue are in the interval of 240 to 840 nm [6], the design was done by using off-the-shelf aluminum mirrors with a UV-enhanced coating for both collimating and focusing purposes to cover this range with sub-Angstrom resolution. Both collimating and focusing mirrors were chosen with the same radius of curvature and declination angle (opposite direction) to cancel the coma. In this antiparallel configuration, the second parabolic mirror largely eliminates the aberrations from the first one. Moreover, we positioned the Echelle grating under the condition of quasi-Littrow design to have high diffraction efficiency with an off-axis angle in the horizontal plane. A ruled reflection grating with dispersion perpendicular to that of the Echelle grating was utilized as a cross dispenser (order separator) after the Echelle grating to distinguish the overlapping diffraction harmonics. The spectrometer has been connected to a gated ICCD to measure time-resolved spectra. The developed spectrometer was installed on a 3-tier utility cart, the inducing laser (Q-switched Nd:YAG) for LIBS was placed on the middle tier, and the last tier was dedicated for calibration instruments (a NIST traceable balanced Deuterium-Halogen light source for intensity calibration, and some gas/vapor spectral lamps including Mercury-Argon, Argon, Neon, and Krypton for wavelength calibration). The portability feature of this LIBS setup provides a remarkable value for testing and characterizing different biological samples on-site. This is a great capability especially if the target sample has the potential of being contagious. This setup is meant to be used for so-called smart laser osteotomies, i.e., the osteotome will be able to identify the type of the tissue being cut through the feedback provided by LIBS [6-8]

All fiber-based LIBS feedback system for endoscopic laser surgery

There has been a particular interest to use laser-induced breakdown spectroscopy (LIBS) as a feedback mechanism for laser surgeries in the past decade 1-6. However, none of the mentioned setups 1-6 is suitable for endoscopic applications due to their bulky free-space configurations. In minimally nvasive surgeries, the major challenge is to integrate ablating laser waveguides and also all sensors inside the narrow channel of the endoscope. In this paper, we present a LIBS setup, which uses a multimode silica fiber for both delivering the inducing laser pulse and collecting the plasma emission light through the endoscope. The fiber-based LIBS setup consists of a frequency-doubled Q-switched Nd:YAG laser (Q-smart 450, Quantel, 532 nm, 5 ns, 60 mJ, 1 Hz), a cleaved large-core silica fiber (1.5 m-long, 1500 um-core, 0.39-NA, 70 mm-bending radius), and an in-house Echelle spectrometer (See Fig. 1). A 75 cm plano-convex laser line lens (Thorlabs, LA1978-YAG) was used to couple the laser beam into a multimode step-index silica fiber. Such a long focal length convex lens was used to avoid breakdown process in air. Moreover, the input face of the fiber was placed at 1 cm behind the focal point to maintain the laser power density below the damage threshold of the fiber. Two tight focusing lenses were placed in front of the fiber end face to collimate the highly divergent laser beam and refocus it onto the sample surface. The light emitted from the microplasma generated at the surface of the sample (bone and its surrounding soft tissues) was collected by the same optics and directed to the spectrometer for characterization. The performance of the developed fiber-based LIBS setup for classification of different tissues has been investigated and compared with the free-space LIBS. The feedback provided by this fiber-based LIBS setup can be used in minimally invasive laserosteotomies in order to stop the laser before causing any collateral damage to surrounding tissues. References [1] F. Yueh, H. Zheng, J.P. Singh, S. Burgess, Preliminary evaluation of laser-induced breakdown spectroscopy for tissue classification, Spectrochim. Acta B 64 (2009) 1059-1067. [2] R. Kanawade, F. Mehari, C. Knipfer, M. Rohde, K. Tangermann-Gerk, et al., Pilot study of laser induced breakdown spectroscopy for tissue differentiation by monitoring the plume created during laser surgery-An approach on a feedback Laser control mechanism, Spectrochim. Acta B 87 (2013) 175-181. [3] K. Henn, G.G. Gubaidullin, J. Bongartz, J. Wahrburg, H. Roth, et al., A spectroscopic approach to monitor the cut processing in pulsed laser osteotomy, Lasers Med. Sci. 28 (2013) 87-92. [4] H. Huang, L.-M. Yang, S. Bai, J. Liu, Smart surgical tool, J. Biomed. Opt. 20 (2015) 028001. [5] R.K. Gill, Z.J. Smith, C. Lee, S. Wachsmann-Hogiu, The effects of laser repetition rate on femtosecond laser ablation of dry bone: a thermal and LIBS study, J. Biophotonics 9 (2016) 171-180. [6] H. Abbasi, G. Rauter, R. Guzman, P.C. Cattin, A. Zam, Laser-induced breakdown spectroscopy as a potential tool for auto carbonization detection in laserosteotomy, J. Biomed. Opt. 23 (2018) 071206

Validation of Non-Restrictive Inertial Gait Analysis of Individuals with Incomplete Spinal Cord Injury in Clinical Settings

Inertial Measurement Units (IMUs) have gained popularity in gait analysis and human motion tracking, and they provide certain advantages over stationary line-of-sight-dependent Optical Motion Capture (OMC) systems. IMUs appear as an appropriate alternative solution to reduce dependency on bulky, room-based hardware and facilitate the analysis of walking patterns in clinical settings and daily life activities. However, most inertial gait analysis methods are unpractical in clinical settings due to the necessity of precise sensor placement, the need for well-performed calibration movements and poses, and due to distorted magnetometer data in indoor environments as well as nearby ferromagnetic material and electronic devices. To address these limitations, recent literature has proposed methods for self-calibrating magnetometer-free inertial motion tracking, and acceptable performance has been achieved in mechanical joints and in individuals without neurological disorders. However, the performance of such methods has not been validated in clinical settings for individuals with neurological disorders, specifically individuals with incomplete Spinal Cord Injury (iSCI). In the present study, we used recently proposed inertial motion-tracking methods, which avoid magnetometer data and leverage kinematic constraints for anatomical calibration. We used these methods to determine the range of motion of the Flexion/Extension (F/E) hip and Abduction/Adduction (A/A) angles, the F/E knee angles, and the Dorsi/Plantar (D/P) flexion ankle joint angles during walking. Data (IMU and OMC) of five individuals with no neurological disorders (control group) and five participants with iSCI walking for two minutes on a treadmill in a self-paced mode were analyzed. For validation purposes, the OMC system was considered as a reference. The mean absolute difference (MAD) between calculated range of motion of joint angles was 5.00°, 5.02°, 5.26°, and 3.72° for hip F/E, hip A/A, knee F/E, and ankle D/P flexion angles, respectively. In addition, relative stance, swing, double support phases, and cadence were calculated and validated. The MAD for the relative gait phases (stance, swing, and double support) was 1.7%, and the average cadence error was 0.09 steps/min. The MAD values for RoM and relative gait phases can be considered as clinically acceptable. Therefore, we conclude that the proposed methodology is promising, enabling non-restrictive inertial gait analysis in clinical settings

Toward finding the best machine learning classifier for LIBS-based tissue differentiation

Lasers have become generally accepted devices in surgical applications, especially as a cutting tool, for cutting both soft and hard tissues including bone (laserosteotomy). It has been shown that applying lasers in osteotomy have important advantages over mechanical tools, including faster healing, more precise cut and functional cutting geometries as well as less trauma [1, 2]. However, the ability of detecting the type of tissue that being cut during surgery can extend the application and safety of laserosteotomes in practice. As a result, the laser could be stopped automatically in case of cutting a tissue that should be preserved. Authors have previously demonstrated that laser-induced breakdown spectroscopy (LIBS) is a potential candidate to differentiate surrounding soft tissue from the bone in ex vivo condition [3]. In the current study, different machine learning classifiers were examined to find the best possible method to differentiate bone from soft tissues based on LIBS data. These methods include decision tree, K Nearest Neighbor (KNN), linear and quadratic Support Vector Machine (SVM) as well as linear and quadratic discriminant analysis. All classifiers were applied on LIBS data obtained from bone, muscle, and fat tissues using an Nd:YAG laser and an Echelle spectrometer. Confusion matrix and Receiver Operating Characteristic (ROC) curve were obtained for each classifier afterwards. Moreover, in order to estimate the model's performance on new data and also to protect the model against overfitting, cross-validation was applied. All mentioned examinations were performed with MATLAB (R2017b)

Flow, force, behaviour: assessment of a prototype hydraulic barrier for invasive fish

Migration barriers being selective for invasive species could protect pristine upstream areas. We designed and tested a prototype protective barrier in a vertical slot fish pass. Based on the individuals’ swimming responses to the barrier flow field, we assumed this barrier would block the ascension of the invasive round goby, but allow comparable native species (gudgeon and bullhead) to ascend. The barrier was tested in three steps: flow description, quantification of forces experienced by preserved fish in the flow field, and tracking the swimming trajectories of ca. 43 live fish per trial and species. The flow and the forces were homogenous over the barrier, though gudgeon experienced significantly smaller forces than round goby or bullhead. The swimming trajectories were distinct enough to predict the fish species with a random forest machine learning approach (92.16% accuracy for gudgeon and 85.24% for round goby). The trajectories revealed round goby and gudgeon exhibited increased, but varied, swimming speeds and straighter paths at higher water discharge. These results suggest that passage of round goby was prevented at 130 L/s water discharge, whereas gudgeon and bullhead could pass the barrier. Our findings open a new avenue of research on hydraulic constructions for species conservation

Impact of hydraulic forces on the passage of round goby (Neogobius melanostomus), gudgeon (Gobio gobio) and bullhead (Cottus gobio) in a vertical slot fish pass

Every fish migrating upstream through vertical slot fish passes must swim through slots, where the resistance force of flowing water could affect the passage success. We measured the hydraulic force acting on the body of preserved benthic fish in a vertical slot at different water discharge rates (80 and 130 L/s) to compare the hydraulic burden individual fish species (round goby Neogobius melanostomus Pallas, 1814, gudgeon Gobio gobio L. and bullhead Cottus gobio L.) must overcome. The forces measured in three spatial axes were then compared to acoustic Doppler velocity measurements and the passage probability of 39–45 live fish per species. Passage probability reduction of 28.26% for round goby and 39.29% for bullhead was observed at the higher water discharge. Gudgeon showed increased numbers of passages and approaches when larger hydraulic forces were experienced at 130 L/s compared to the lower water discharge. Gudgeon experienced significantly lower hydraulic forces (mean 0.27 N ± 0.12 standard deviation) compared to round goby (mean 0.32 N ± 0.12 SD) and bullhead (0.35 N ± 0.14 SD). Potentially, the increased hydraulic forces at the higher water discharge contributed to the reduction in passages in round goby and bullhead. That gudgeon behaved differently from the other species illustrates how fish species deal differently with flowing water and the hydraulic forces experienced. Our approach provides a species-oriented assessment of the flow field in ecologically relevant fish passes. These findings represent an important step towards the development of purposeful fish pass designs, which is essential for ecosystem-oriented river connectivity

Machine learning-based method for linearization and error compensation of an absolute rotary encoder

The main objective of this work is to develop a miniaturized, high accuracy, single-turn absolute, rotary encoder called ASTRAS360. Its measurement principle is based on capturing an image that uniquely identifies the rotation angle. To evaluate this angle, the image first has to be classified into its sector based on its color, and only then can the angle be regressed. In-spired by machine learning, we built a calibration setup, able to generate labeled training data automatically. We used these training data to test, characterize, and compare several machine learning algorithms for the classification and the regression. In an additional experiment, we also characterized the tolerance of our rotary encoder to eccentric mounting. Our findings demonstrate that various algorithms can perform these tasks with high accuracy and reliability; furthermore, providing extra-inputs (e.g. rotation direction) allows the machine learning algorithms to compensate for the mechanical imperfections of the rotary encoder.Comment: This paper was submitted for publication to Measurement (Elsevier) on the 7th July 202

Proof of concept of a novel absolute rotary encoder

Rotary encoders are used in many applications that require monitoring or controlling mechanical systems such as robots. Typically, small rotary encoders have poor resolution; this is unfortunate for applications such as robotics in medical surgery procedures. For example, in an articulated robotic endoscope, miniaturization is mandatory and, when automation is desired, high accuracy to track the shape and pose of the device is required; small (few millimeters) and accurate (few hundred arcsec) rotary encoders are thus needed. Previously, we introduced a novel concept of a miniaturizable angular sensor, called ASTRAS (Angular Sensor for TRAcking System). This was presented as a basic element of a tracking system for articulated endoscopes. The principle of measurement of ASTRAS is based on processing a shadow image cast by a shadow mask onto an image sensor. The characterization of the first prototype of ASTRAS was very promising, however, its angular range of about ±30 degrees was too limiting for many practical applications. In this work, we present an extension of the concept mentioned above to a rotary encoder that can measure one full rotation of 360 degrees thus the name is ASTRAS360. Its working principle bases on encoding the shadow image using colored light to distinguish different angular sectors. The identification of the sector corresponds to a coarse angular measurement, which is afterward refined using the same technique as in ASTRAS. We implemented this concept, realizing a prototype and an algorithm to calculate the angle from the shadow image. The experiments demonstrated the validity of this concept and showed encouraging results with a precision of ∼0.6 arcsec and 6σ-resolution of 3.6 arcsec corresponding to 19 bits