iDeLog: Iterative Dual Spatial and Kinematic Extraction of Sigma-Lognormal Parameters

The Kinematic Theory of rapid movements and its associated Sigma-Lognormal model have been extensively used in a large variety of applications. While the physical and biological meaning of the model have been widely tested and validated for rapid movements, some shortcomings have been detected when it is used with continuous long and complex movements. To alleviate such drawbacks, and inspired by the motor equivalence theory and a conceivable visual feedback, this paper proposes a novel framework to extract the Sigma-Lognormal parameters, namely iDeLog. Specifically, iDeLog consists of two steps. The first one, influenced by the motor equivalence model, separately derives an initial action plan defined by a set of virtual points and angles from the trajectory and a sequence of lognormals from the velocity. In the second step, based on a hypothetical visual feedback compatible with an open-loop motor control, the virtual target points of the action plan are iteratively moved to improve the matching between the observed and reconstructed trajectory and velocity. During experiments conducted with handwritten signatures, iDeLog obtained promising results as compared to the previous development of the Sigma-Lognormal.Comment: Accepted Version published by Transactions on Pattern Analysis and Machine Intelligenc

Towards Stroke Patients' Upper-limb Automatic Motor Assessment Using Smartwatches

Assessing the physical condition in rehabilitation scenarios is a challenging problem, since it involves Human Activity Recognition (HAR) and kinematic analysis methods. In addition, the difficulties increase in unconstrained rehabilitation scenarios, which are much closer to the real use cases. In particular, our aim is to design an upper-limb assessment pipeline for stroke patients using smartwatches. We focus on the HAR task, as it is the first part of the assessing pipeline. Our main target is to automatically detect and recognize four key movements inspired by the Fugl-Meyer assessment scale, which are performed in both constrained and unconstrained scenarios. In addition to the application protocol and dataset, we propose two detection and classification baseline methods. We believe that the proposed framework, dataset and baseline results will serve to foster this research field

Exploring the Potential of Robot-Collected Data for Training Gesture Classification Systems

Sensors and Artificial Intelligence (AI) have revolutionized the analysis of human movement, but the scarcity of specific samples presents a significant challenge in training intelligent systems, particularly in the context of diagnosing neurodegenerative diseases. This study investigates the feasibility of utilizing robot-collected data to train classification systems traditionally trained with human-collected data. As a proof of concept, we recorded a database of numeric characters using an ABB robotic arm and an Apple Watch. We compare the classification performance of the trained systems using both human-recorded and robot-recorded data. Our primary objective is to determine the potential for accurate identification of human numeric characters wearing a smartwatch using robotic movement as training data. The findings of this study offer valuable insights into the feasibility of using robot-collected data for training classification systems. This research holds broad implications across various domains that require reliable identification, particularly in scenarios where access to human-specific data is limited

MDIW 13: A new multi lingual and multi script database and benchmark for script identification

Script identification plays a vital role in applications that involve handwriting and document analysis within a multi-script and multi-lingual environment. Moreover, it exhibits a profound connection with human cognition. This paper provides a new database for benchmarking script identification algorithms, which contains both printed and handwritten documents collected from a wide variety of scripts, such as Arabic, Bengali (Bangla), Gujarati, Gurmukhi, Devanagari, Japanese, Kannada, Malayalam, Oriya, Roman, Tamil, Telugu, and Thai. The dataset consists of 1,135 documents scanned from local newspaper and handwritten letters as well as notes from different native writers. Further, these documents are segmented into lines and words, comprising a total of 13,979 and 86,655 lines and words, respectively, in the dataset. Easy-to-go benchmarks are proposed with handcrafted and deep learning methods. The benchmark includes results at the document, line, and word levels with printed and handwritten documents. Results of script identification independent of the document/line/word level and independent of the printed/handwritten letters are also given. The new multi-lingual database is expected to create new script identifiers, present various challenges, including identifying handwritten and printed samples and serve as a foundation for future research in script identification based on the reported results of the three benchmarksOpen Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This study was funded by the Spanish government’s PID2019-109099RB-C41 research project and European Union FEDER program/fund

Kinematic Synthesis for 3D Signatures

© 2022 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper proposes a method to generate the synthetic kinematic of signatures in 3D. The analysis of 3D signatures is becoming a hot topic due to the irruption of commercial off-the-shelf devices for easy acquisition of 3D movements. However, the novelty of this technology reveals the scarce publicly available signatures in 3D, which hinder their development. A solution is the synthesis of Signatures in 3D. As a first step, this paper synthesizes the kinematics of 3D signatures based on the Kinematic Theory of Rapid Movements and its associated Sigma-Lognormal model in 3D. To evaluate the method, we regenerate signature databases with synthetic speed profiles in all genuine and forgeries found in two 3D signature databases. Then, we analyze the similarities in the performance of a signature verifier when real and synthetic signatures are used in random and skilled forgeries experiments.This study was funded by the Spanish government’s MIMECO PID2019-109099RB-C41 research project and European Union FEDER program/funds, the CajaCanaria and la Caixa bank grant 2019SP19, and NSERC grant RGPIN-2015-06409

Multiple generation of Bengali static signatures

Handwritten signature datasets are really necessary for the purpose of developing and training automatic signature verification systems. It is desired that all samples in a signature dataset should exhibit both inter-personal and intra-personal variability. A possibility to model this reality seems to be obtained through the synthesis of signatures. In this paper we propose a method based on motor equivalence model theory to generate static Bengali signatures. This theory divides the human action to write mainly into cognitive and motor levels. Due to difference between scripts, we have redesigned our previous synthesizer [1,2], which generates static Western signatures. The experiments assess whether this method can approach the intra and inter-personal variability of the Bengali-100 Static Signature DB from a performance-based validation. The similarities reported in the experimental results proof the ability of the synthesizer to generate signature images in this script

The RPM3D project: 3D Kinematics for Remote Patient Monitoring

This project explores the feasibility of remote patient monitoring based on the analysis of 3D movements captured with smartwatches. We base our analysis on the Kinematic Theory of Rapid Human Movement. We have validated our research in a real case scenario for stroke rehabilitation at the Guttmann Institute5 (neurorehabilitation hospital), showing promising results. Our work could have a great impact in remote healthcare applications, improving the medical efficiency and reducing the healthcare costs. Future steps include more clinical validation, developing multi-modal analysis architectures (analysing data from sensors, images, audio, etc.), and exploring the application of our technology to monitor other neurodegenerative diseases

Ultra-Low Power Sensor Devices for Monitoring Physical Activity and Respiratory Frequency in Farmed Fish

Integration of technological solutions aims to improve accuracy, precision and repeatability in farming operations, and biosensor devices are increasingly used for understanding basic biology during livestock production. The aim of this study was to design and validate a miniaturized tri-axial accelerometer for non-invasive monitoring of farmed fish with re-programmable schedule protocols. The current device (AE-FishBIT v.1s) is a small (14 mm × 7 mm × 7 mm), stand-alone system with a total mass of 600 mg, which allows monitoring animals from 30 to 35 g onwards. The device was attached to the operculum of gilthead sea bream (Sparus aurata) and European sea bass (Dicentrarchus labrax) juveniles for monitoring their physical activity by measurements of movement accelerations in x- and y-axes, while records of operculum beats (z-axis) served as a measurement of respiratory frequency. Data post-processing of exercised fish in swimming test chambers revealed an exponential increase of fish accelerations with the increase of fish speed from 1 body-length to 4 body-lengths per second, while a close relationship between oxygen consumption (MO2) and opercular frequency was consistently found. Preliminary tests in free-swimming fish kept in rearing tanks also showed that device data recording was able to detect changes in daily fish activity. The usefulness of low computational load for data pre-processing with on-board algorithms was verified from low to submaximal exercise, increasing this procedure the autonomy of the system up to 6 h of data recording with different programmable schedules. Visual observations regarding tissue damage, feeding behavior and circulating levels of stress markers (cortisol, glucose, and lactate) did not reveal at short term a negative impact of device tagging. Reduced plasma levels of triglycerides revealed a transient inhibition of feed intake in small fish (sea bream 50–90 g, sea bass 100–200 g), but this disturbance was not detected in larger fish. All this considered together is the proof of concept that miniaturized devices are suitable for non-invasive and reliable metabolic phenotyping of farmed fish to improve their overall performance and welfare. Further work is underway for improving the attachment procedure and the full device packaging

El uso de energía en microempresas tradicionales. Eficiencia, innovación y gestión

Cualquiera que sepa que las microempresas en Medellín, actualmente suman cerca de 95.000 -algo así como el 96% del tejido empresarial-, y que generan alrededor del 50% del empleo de la ciudad, le interesará este libro. La razón es simple: en él se ofrecen modos muy concretos, no sólo de conservarlas sino de fortalecerlas. Haga el lector el siguiente ejercicio: cierre los ojos e imagine qué le ocurriría a la ciudad y a miles de sus familias si por algún albur, todas -o la mayoría- de las microempresas desaparecieran de repente. Seguramente lo que vería, no sería agradable, entonces abra los ojos y dispóngase a leer esta obra.El mensaje básico del presente libro es que usar eficientemente la energía, representa para todas las empresas, pero en particular para las micronegocios, beneficios no sólo en productividad y competitividad sino también en seguridad ocupacional y bienestar para sus dueños, sus familias y empleados, además de favorecer el medio ambiente. Alcanzar la eficiencia energética se logra tanto por disponer y adoptar buenas tecnologías energéticas, adecuadas instalaciones y espacios apropiados para su explotación, como gracias a las mejoras en los comportamientos y estilos de vida de los usuarios frente al consumo de las diversas fuentes de energía: hidroeléctrica, gas, carbón, leña, etc. En consecuencia, en esta obra se ofrecen a los microempresarios de estratos populares de la ciudad de Medellín, tanto alternativas tecnológicas y socioeconómicas que les permitan ser más eficientes y productivos, como un modelo de gestión energética que las haga viables y sostenibles en el tiempo.La conclusión del libro es clara: sin microempresas podrá haber crecimiento económico, pero nunca desarrollo humano incluyente y sostenible.  La novedad de la obra radica precisamente en que nunca antes las microempresas en el país habían sido conocidas y evaluadas desde el punto de vista de su eficiencia energética y menos aún, se habían hecho propuestas alcanzables para su mejoramiento y fortalecimiento.No sobra agregar que en su concepción y composición, en el libro participó un amplio grupo de académicos e investigadores de renombradas universidades de la ciudad, lo mismo que expertos y consultores tanto públicos como privados. Pero, sobre todo, este libro no hubiera sido posible sin la presencia constante y activa de los microempresarios que aportaron toda su buena voluntad para llevar a cabo el proyecto de investigación que le dio origen a la obra. A todos ellos se les hace un merecido reconocimiento a lo largo y ancho de sus páginas