Smart object for physical rehabilitation assessment

The technologies associated with smart healthcare are a reality nowadays, however in the physical therapy area there is still lack of patient monitoring during the physical rehabilitation and common usage of walking aids by the patients affected by lower limb impairments. Currently there are fewer systems that provide the patient monitoring during the rehabilitation process by physiotherapists, which may lead to less adequate diagnostic techniques for the patient's physical condition. The dissertation presents a solution to this problem by relying on smart equipment used in physical rehabilitation, more precisely a crutch. By embedding multiple smart sensors on crutches, the physiotherapist will be provided appropriate information regarding the interaction between the patient and the walking aids through a mobile application, developed for Android systems, which will receive data from the sensors via Bluetooth. All the data collected will be stored in a local database located on the physiotherapist’s mobile device and also on a remote server, giving the possibility of having a full offline application. This system allows for any session previously done to be consulted, which results in the possibility of visualizing historical values and comparing them with different sessions, allowing the physiotherapist to analyze the evolution of the patients.As tecnologias associadas à saúde são uma realidade na atualidade, porém na área de fisioterapia ainda há falta de monitorização dos pacientes durante a fisioterapia e o uso de objetos que auxiliam o movimento pelos pacientes afetados por deficiências nos membros inferiores. Atualmente, existem poucos sistemas que proporcionam a monitorização do paciente durante o processo de reabilitação por fisioterapeutas, o que pode levar a técnicas de diagnóstico menos adequadas para a condição física do paciente. A dissertação apresenta uma solução para este problema, contando com equipamentos inteligentes utilizados em fisioterapia, mais precisamente uma muleta. Ao incorporar vários sensores inteligentes em muletas, o fisioterapeuta receberá informações adequadas sobre a interação entre o paciente e as muletas através de uma aplicação móvel, desenvolvida para sistemas Android, que receberá dados dos sensores via Bluetooth. Todos os dados recebidos serão armazenados numa base de dados local localizada no dispositivo móvel do fisioterapeuta e também num servidor remoto para fins de sincronização, dando a possibilidade de ter um uma aplicação completamente offline

Providing Real-Time Exercise Feedback to Patients Undergoing Physical Therapy

Musculoskeletal conditions, often requiring rehabilitation, affect one-third of the U.S. population annually. RehabBuddy is a rehabilitation assistance system that extends the reach of a physical rehabilitation specialist beyond the clinic. This thesis presents a system that uses body-worn motion sensors and a mobile application that provides the patient with assistance to ensure that home exercises are performed with the same precision as under clinical supervision. Assisted by a specialist in the clinic, the wearable sensors and user interface developed allow the capture of individualized exercises unique to the patient's physical abilities. Beyond the clinical setting, the system can assist patients by providing real-time corrective feedback to repeat these exercises through a correct and complete arc of motion for the prescribed number of repetitions. An inertial measurement unit (IMU) is used on the body part to be exercised to capture its pose. Presented is a kinematics data processing approach to defining custom exercises with flexibility in terms of where it is worn and the nature of the exercise, as well as real-time corrective feedback parameters. This thesis goes through the engineering approach, initial student investigator trials, and presents new preliminary subject data from subject trials currently ongoing at the University of Kentucky. The system is tested on multiple exercises performed by multiple subjects. It is then demonstrated how it can improve exercise adherence by assisting patients in reaching the full prescribed range of motion and avoid overextension, assist in adherence to the ideal plane of motion, and affect hold time.MSComputer Engineering, College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/169159/1/Ella Reimann Final Thesis.pd

IoPhyR - physical rehabilitation IoT system: sistema de reabilitação motora baseado em andarilhos inteligentes e IoT

A presente dissertação descreve o desenvolvimento de um sistema IoT (Internet of Things) de reabilitação física baseado em smart walkers. O sistema inclui sensores de tipo IMU (Inertial Measurement Unit), sensores de força (células de carga), e sensores de proximidade (sensores de ultrassons). Os sinais adquiridos por uma plataforma de computação com microcontrolador ligada aos sensores permitem calcular métricas associadas a caracterização da orientação e do equilíbrio do paciente, assim como elementos relacionados com a utilização do andarilho como a elevação do mesmo, o número de passos efetuados e a força exercida sobre os pés do andarilho. O smart walker utiliza a plataforma de computação de tipo Arduino Mega para a realização do cálculo de métricas ligadas a caracterização das sessões de fisioterapia que serão posteriormente armazenadas na nuvem. Os dados adquiridos ao nível dos smart walkers são transmitidos para a nuvem do sistema, utilizando um módulo Wi-Fi, ou por intermédio de um tablet que recebe os dados da sessão em curso através de comunicação Bluetooth, sendo realizada uma sincronização de dados tablet-nuvem.A análise e visualização dos dados armazenados é realizada através da webapp e aplicação móvel desenvolvidas.This dissertation describes the development of an Arduino based physical rehabilitation IoT system. The system uses metrics acquired from IMU sensors (Inertial Measurement Unit), pressure sensors (load cells) and distance sensors (ultrasound sensors). The metrics extracted from these sensors help to determine the patient’s orientation, the number of steps taken, and the patient’s balance. The smart walker uses the Arduino Mega platform to calculate the required metrics during the physiotherapy sessions to store them in the system cloud server afterwards. The cloud server storing process is done straight from the smart walker, using a Wi-Fi module, or through a mobile device with the system’s mobile app, using a Bluetooth module. The stored data analysis and visualization is performed through the developed system’s user interfaces (a webapp and a mobile app)

Adaptive Energy Saving and Mobility Support IPv6 Routing Protocol in Low-Power and Lossy Networks for Internet of Things and Wireless Sensor Networks

Internet of Things (IoT) is an interconnection of physical objects that can be controlled, monitored and exchange information from remote locations over the internet while been connected to an Application Programme Interface (API) and sensors. It utilizes low-powered digital radios for communication enabling millions and billions of Low-power and Lossy Network (LLN) devices to communicate efficiently via a predetermined routing protocol. Several research gaps have identified the constraints of standardised versions of IPv6 Routing Protocol for Low Power and Lossy Networks evidently showing its lack of ability to handle the growing application needs and challenges. This research aims to handle routing from a different perspective extending from energy efficiency, to mobility aware and energy scavenging nodes thereby presenting numerous improvements that can suit various network topologies and application needs. Envisioning all the prospects and innovative services associated with the futuristic ubiquitous communication of IoT applications, we propose an adaptive Objective Function for RPL protocol known as Optimum Reliable Objective Function (OR-OF) having a fuzzy combination of five routing metrics which are chosen based on system and application requirements. It is an approach which combines the three proposed implemented Objective Functions within this thesis to enable the OR-OF adapt to different routing requirements for different IoT applications. The three proposed OFs are Energy saving Routing OF, Enhanced Mobility Support Routing OF and Optimized OF for Energy Scavenging nodes. All proposed OFs were designed, implemented, and simulated in COOJA simulator of ContikiOS, and mathematical models were developed to validate simulated results. Performance Evaluation indicated an overall improvement as compared with the standardised versions of RPL protocols and other related research works in terms of network lifetime with an average of 40%, packet delivery ratio of 21%, energy consumption of 82% and End-to-End Delay of 92%