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Análise da duração do ciclo de marcha com recurso a wearable sensor baseado nas tecnologias LiDAR e IoT
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Resumo(s)
A prescrição e avaliação de próteses do membro inferior baseiam-se predominantemente em critérios empíricos e subjetivos, podendo resultar na aplicação de próteses não otimizadas às necessidades individuais dos utentes, contribuindo para o desperdício de recursos e elevados custos para os sistemas de saúde. A falta de acesso a Instrumentos de Medição e Avaliação limita a tomada de decisão baseada em evidência, bem como a implementação de intervenções individualizadas e sustentáveis. A marcha assimétrica está associada a custos energéticos elevados, desgaste articular precoce devido à maior solicitação do membro contralateral, ao alinhamento incorreto das próteses e à sua adaptação inadequada. A análise objetiva depende geralmente de equipamentos complexos, volumosos ou dispendiosos, dificultando a sua aplicação em contextos clínicos do dia-a-dia. Este estudo propõe um dispositivo wearable baseado num sensor LiDAR, um microcontrolador e o recurso a tecnologias IoT, para uma avaliação quantitativa dos parâmetros da marcha, nomeadamente a duração do ciclo de marcha e a simetria dos membros inferiores. Como prova de conceito os testes foram realizados com o sensor TF mini-S LiDAR e o microcontrolador Arduino Nano RP2040 Connect. O sensor, posicionado na face interna da perna, deteta a fase do apoio médio – momento em que o membro contralateral cruza o plano sagital. Combinado com o Arduino Nano RP2040, o sistema processa dados em tempo real, calculando a Duração do Ciclo de Marcha e quantificando assimetrias entre os membros inferiores, através do Índice de Simetria e da Razão de Simetria. O dispositivo, de dimensões reduzidas, incorpora conetividade Wi-Fi e tecnologias IoT, permitindo a transmissão, controlo e visualização remota dos dados no Arduino Cloud. Visa a avaliação objetiva contínua em ambientes não laboratoriais, o suporte a decisões clínicas, a seleção de componentes protésicos e a promoção da sustentabilidade dos sistemas de saúde, melhorando a qualidade de vida dos amputados e definindo padrões de reabilitação baseados em evidência e acessibilidade.
Abstract The prescription and evaluation of lower limb prostheses are predominantly based on empirical and subjective criteria, which may result in the use of prostheses not optimized for individual patient needs, contributing to resource waste and high healthcare costs. The lack of access to measurement and evaluation tools limits evidence-based decision-making and the implementation of custom-made, sustainable interventions. Asymmetric gait is associated with high energy expenditure, premature joint wear due to increased load on the contralateral limb, and with incorrect alignment and inadequate adaptation of prostheses. Objective analysis typically depends on complex, bulky, and expensive equipment, which limits its application in daily clinical settings. This study proposes a wearable device integrating a LiDAR sensor, a microcontroller and IoT technologies, to provide quantitative evaluation of gait parameters such as gait cycle duration and lower limb symmetry. As a proof of concept, tests were performed with the TF mini-S LiDAR sensor and the Arduino Nano RP2040 Connect microcontroller. The TF mini–S LiDAR sensor is positioned on the medial side of the leg and detects the mid-stance phase—when the contralateral limb crosses the sagittal plane. Combined with the Arduino Nano RP2040 Connect, the system processes real-time data to calculate gait cycle duration and quantify asymmetries between the left and right lower limbs using the Symmetry Index and Symmetry Ratio. This combination enables the development of a compact device featuring Wi-Fi connectivity and IoT technologies for remote data transmission, control, and visualization via the Arduino Cloud Dashboard. The device offers a solution for evaluating objective metrics, allowing continuous monitoring in non-laboratory environments, supporting clinical decisions with quantifiable data, aiding prosthetic component selection, and promoting health system sustainability. The technology aims to enhance amputees’ quality of life and to set rehabilitation standards by prioritizing evidence-based practice, accessibility, and treatments tailored to the specific needs of each individual.
Abstract The prescription and evaluation of lower limb prostheses are predominantly based on empirical and subjective criteria, which may result in the use of prostheses not optimized for individual patient needs, contributing to resource waste and high healthcare costs. The lack of access to measurement and evaluation tools limits evidence-based decision-making and the implementation of custom-made, sustainable interventions. Asymmetric gait is associated with high energy expenditure, premature joint wear due to increased load on the contralateral limb, and with incorrect alignment and inadequate adaptation of prostheses. Objective analysis typically depends on complex, bulky, and expensive equipment, which limits its application in daily clinical settings. This study proposes a wearable device integrating a LiDAR sensor, a microcontroller and IoT technologies, to provide quantitative evaluation of gait parameters such as gait cycle duration and lower limb symmetry. As a proof of concept, tests were performed with the TF mini-S LiDAR sensor and the Arduino Nano RP2040 Connect microcontroller. The TF mini–S LiDAR sensor is positioned on the medial side of the leg and detects the mid-stance phase—when the contralateral limb crosses the sagittal plane. Combined with the Arduino Nano RP2040 Connect, the system processes real-time data to calculate gait cycle duration and quantify asymmetries between the left and right lower limbs using the Symmetry Index and Symmetry Ratio. This combination enables the development of a compact device featuring Wi-Fi connectivity and IoT technologies for remote data transmission, control, and visualization via the Arduino Cloud Dashboard. The device offers a solution for evaluating objective metrics, allowing continuous monitoring in non-laboratory environments, supporting clinical decisions with quantifiable data, aiding prosthetic component selection, and promoting health system sustainability. The technology aims to enhance amputees’ quality of life and to set rehabilitation standards by prioritizing evidence-based practice, accessibility, and treatments tailored to the specific needs of each individual.
Descrição
Palavras-chave
Duração do ciclo de marcha Simetria da marcha LiDAR IoT Wearable sensor Gait cycle duration Gait symmetry