Walking Behavior Change Detector for a “Smart” Walker

AbstractThis study investigates the design of a novel real-time system to detect walking behavior changes using an accelerometer on a rollator. No sensor is required on the user. We propose a new non-invasive approach to detect walking behavior based on the motion transfer by the user on the walker. Our method has two main steps; the first is to extract a gait feature vector by analyzing the three-axis accelerometer data in terms of magnitude, gait cycle and frequency. The second is to classify gait with the use of a decision tree of multilayer perceptrons. To assess the performance of our technique, we evaluated different sampling window lengths of 1, 3 an 5seconds and four different Neural Network architectures. The results revealed that the algorithm can distinguish walking behavior such as normal, slow and fast with an accuracy of about 86%. This research study is part of a project aiming at providing a simple and non-invasive walking behavior detector for elderly who use rollators

Walking Behavior Change Detector for a “Smart” Walker

AbstractThis study investigates the design of a novel real-time system to detect walking behavior changes using an accelerometer on a rollator. No sensor is required on the user. We propose a new non-invasive approach to detect walking behavior based on the motion transfer by the user on the walker. Our method has two main steps; the first is to extract a gait feature vector by analyzing the three-axis accelerometer data in terms of magnitude, gait cycle and frequency. The second is to classify gait with the use of a decision tree of multilayer perceptrons. To assess the performance of our technique, we evaluated different sampling window lengths of 1, 3 an 5seconds and four different Neural Network architectures. The results revealed that the algorithm can distinguish walking behavior such as normal, slow and fast with an accuracy of about 86%. This research study is part of a project aiming at providing a simple and non-invasive walking behavior detector for elderly who use rollators

GERONTECNOLOGIA: O QUE MOSTRA A PRODUÇÃO CIENTÍFICA NOS ÚLTIMOS 20 ANOS?.

RESUMO Este estudo teve como objetivo explorar na literatura científica mundial, publicações sobre gerontecnologia e realizar uma análise destas publicações, buscando evidenciar a evolução temporal, bem como, os eixos temáticos. Foi realizado uma revisão cenciométrica por meio de uma análise da produção científica veiculada em periódicos indexados nas bases de dados SciELO, PubMed, Science Direct e Lilacs. Foi utilizado o descritor gerontecnologia e seu correspondente em inglês e espanhol. Foram identificados e coletados ano de publicação e eixo temático central. Os dados foram tabulados, organizados em planilhas do programa Microsoft Excel 2010 e empregada análise descritiva. Descartando-se as publicações duplicadas, obteve-se um total de 111 artigos científicos eleitos para este estudo. Com relação à evolução temporal foi evidenciado que a primeira publicação sobre o tema gerontologia datou de 1997 e, houve um aumento brusco em 1998, um declínio a zero em 1999, e nos anos seguintes, as publicações apresentam uma tendência a comportamento crescente constante. Já os eixos temáticos foram evidenciados em maior relevância: Mobilidade e Motricidade (16,2%); Cuidados Comunitários e Ambiente, ambos com (15,3%); Capacidades Sensoriais e Cognitivas (10,8%) e Design e Ergonomia (9,9%). Conclui-se que existe uma tendência a implantação da gerontecnologia nos estudos e são distintos os eixos abordados por esta temática, além disso a tecnologia é uma nova abordagem de promover saúde e qualidade de vida aos idosos no contexto da interdisciplinaridade. Palavras-chave: Envelhecimento; Tecnologia; Promoção da Saúde. GERONTECNOLOGY: WHAT SHOWS A SCIENTIFIC PRODUCTION IN THE LAST 20 YEARS? ABSTRACT This study aimed to explore in the scientific literature worldwide, publications on gerontecnologia and to carry out an analysis of these publications, seeking to evidence the temporal evolution, as well as, the thematic axes. A centimeter revision was carried out through an analysis of the scientific production published in journals indexed in the SciELO, PubMed, Science Direct and Lilacs databases. The descriptor gerontecnologia and its correspondent in English and Spanish were used. The year of publication and central theme were identified and collected. The data were tabulated, organized into spreadsheets of the program Microsoft Excel 2010 and employed descriptive analysis. Discarding duplicate publications, we obtained a total of 111 scientific articles chosen for this study. Regarding historical evolution, it was evidenced that the first publication on gerontology dates back to 1997, and there was an abrupt increase in 1998, a decline to zero in 1999, and in the following years, publications show a trend towards steadily increasing behavior. The thematic axes were evidenced in greater relevance: Mobility and Mobility (16.2%); Community Care and Environment, both with (15.3%); Sensory and Cognitive Capabilities (10.8%) and Design and Ergonomics (9.9%). It is concluded that there is a trend towards the implantation of gerontecnologia in the studies and the axes addressed by this theme are distinct, in addition technology is a new approach to promote health and quality of life for the elderly in the context of interdisciplinarity. KEY WORDS: Aging; Technology; Health promotion

Performance of the Intrac Wireless Activity Tracking System for the Afari Assistive Device

Afari is a mobility device that was designed to be more recreational, aesthetic, and functional outside than the typical mobility devices commonly used today such as walkers, crutches, and rollators. The Afari transfers weight from a user through the arm rests and enforces an upright posture while walking with correct adjustments to the arm rest height. In addition to assisting with walking or running, a sensor system fitted to the Afari device has been designed to analyze different aspects of activity tracking such as the dynamic loading applied to the arm rests, spatial-temporal gait parameters, speed, and distance. This includes various sensors, namely, load cells for each arm rest, an inertial measurement unit, and a speed and distance sensor that wirelessly transmit data via Bluetooth Low Energy (BLE) to either a smartphone or computer. The total distance, pitch angle, right and left loading on each armrest can be viewed in real time by the user. An algorithm was created in MATLAB to process all the raw data and compute cadence, stride length, average toe-off and heel strike angle, swing and stance time, and speed over the duration of active use. An Afari user can monitor these different aspects of their activity and adjust accordingly to potentially improve their balance or gait

Desarrollo modular de un andador inteligente

En la actualidad muchos esfuerzos de investigación en el campo de la robótica y la electrónica están muy enfocados en mejorar el bienestar personal, en especial el de las personas mayores. Muchas áreas de la ingeniería se ven involucradas en este proceso de creación de dispositivos que hagan la vida mucho más sencilla, como son el control, la mecánica, los sistemas electrónicos y de medidas, entre otros. El presente proyecto comprende la modificación de un andador convencional, incorporando en el mismo distintos módulos que permitan la autonomía y la realización de ciertas tareas, transformándolo en un andador inteligente. Para realizar este objetivo se implementará un sistema de motorización y un sistema de seguimiento del usuario, el cual permitirá una constante monitorización de la velocidad de desplazamiento del mismo y de esta manera ajustar su propia velocidad. También se incorporará un sistema de teleoperación que cuenta con tres métodos alternativos para poder dirigir mediante ordenes al andador: un dispositivo móvil utilizando un joystick para indicar la dirección deseada; micrófonos para detectar la posición según el ángulo de procedencia de determinado sonido emitido por el usuario; y un sistema de reconocimiento de comandos de voz. Para lograr implementar estas funciones se hará uso de un microcontrolador programable, a través de Arduino IDE, el cual constituirá el centro de control del andador.Currently, many research efforts in the field of robotics and electronics are focused on improving personal well-being, especially for the elderly. Many areas of engineering are involved in this process of creating devices that make life much easier, such as control, mechanics, electronic and measurement systems, among others. This project includes the modification of a conventional walker, incorporating different modules that allow autonomy and the performance of certain tasks, transforming it into an intelligent walker. To achieve this objective, a motorization system and a user tracking system will be implemented, which will allow constant monitoring of the user's movement speed and thus adjust his own speed. A teleoperation system will also be incorporated, which has three alternative methods for directing by means of orders to the walker: a mobile device using a joystick to indicate the desired direction; microphones to detect the position according to the angle of the origin of a certain sound emitted by the user; and a voice command recognition system. In order to implement these functions, a programmable microcontroller will be used through Arduino IDE, which will be the control center of the walker.Departamento de Ingeniería de Sistemas y AutomáticaMáster en Electrónica Industrial y Automátic

Walking behavior change detector for a “smart” walker

This study investigates the design of a novel real-time system to detect walking behavior changes using an accelerometer on a rollator. No sensor is required on the user. We propose a new non-invasive approach to detect walking behavior based on the motion transfer by the user on the walker. Our method has two main steps; the first is to extract a gait feature vector by analyzing the three-axis accelerometer data in terms of magnitude, gait cycle and frequency. The second is to classify gait with the use of a decision tree of multilayer perceptrons. To assess the performance of our technique, we evaluated different sampling window lengths of 1, 3 an 5 seconds and four different Neural Network architectures. The results revealed that the algorithm can distinguish walking behavior such as normal, slow and fast with an accuracy of about 86%. This research study is part of a project aiming at providing a simple and non-invasive walking behavior detector for elderly who use rollators

Walking behavior change detector for a "smart" walker : 6th International conference on Intelligent Human Computer Interaction, IHCI 2014

This study investigates the design of a novel real-time system to detect walking behavior changes using an accelerometer on a rollator. No sensor is required on the user. We propose a new non-invasive approach to detect walking behavior based on the motion transfer by the user on the walker. Our method has two main steps; the first is to extract a gait feature vector by analyzing the three-axis accelerometer data in terms of magnitude, gait cycle and frequency. The second is to classify gait with the use of a decision tree of multilayer perceptrons. To assess the performance of our technique, we evaluated different sampling window lengths of 1, 3 an 5 seconds and four different Neural Network architectures. The results revealed that the algorithm can distinguish walking behavior such as normal, slow and fast with an accuracy of about 86%. This research study is part of a project aiming at providing a simple and non-invasive walking behavior detector for elderly who use rollators