Application of force and inertial sensors to monitor gait on legacy walkers

Walker assistive devices play an important role in extending the autonomy of elderly people and in recovering the mobility of people affected by locomotion disabilities. The next generation of walkers are hoped to include embedded sensors and data processing capabilities that will allow for the extraction of objective metrics (about gait and body posture) to assist the work of physiotherapists and to enable the self-control nature of walker usage. The paper presents the Andante, our latest proposal of a smart walker intended to monitor and analyze gait in real time. The system makes use of e-textile electrodes to sense the heart rate of the user, load cells to measure the forces applied on the walker legs, and an inertial measurement unit to sense motion and orientation. These signals are sampled locally and transferred over a Bluetooth link to a remote host, where they are processed in real time. Data processing includes the detection, classification, and characterization of the steps. A rich set of parameters is presented for each step, including estimates of balance and motor coordination, step length and azimuth, and lift of the walker frame. This information can be used by physiotherapist to objectively assess the physical condition of the user and tune rehabilitation therapy if needed. The proposed solution can be easily integrated into any commercial walker without any loss of functionality.info:eu-repo/semantics/publishedVersio

A low cost measurement system to extract kinematic parameters from walker devices

Trabalho apresentado no International Instrumentation & Measurement Technology Conference, maio 2015, Pisa, ItáliaThis paper presents a low cost measurement system that can be used to extract kinematic parameters from walker devices. The proposed measurement system can be easily integrated in any commercial non-smart walker device and includes mainly a set of six force sensing resistors and one 3D accelerometer, with the associated signal conditioning circuits, and the data acquisition and processing unit with wireless communication capabilities. The signals that are acquired from the sensors are used to obtain, in real time, the values of several variables related with strength, acceleration and tilt angles that are associated with the usage of walker devices. The proposed measurement system enables the detection of conditions that are related with a deficient usage of the walker device, such as, bad positioning of the walker legs during gait, amplitude and timing unbalances of the forces applied on the walker legs or on the walker hand grips, excessive values of mechanical oscillations or tilt angles of the walker device. Some calibration and experimental results are included in the paper.info:eu-repo/semantics/publishedVersio

Remote sensing technologies for physiotherapy assessment

The paper presents a set of remote, unobtrusive sensing technologies that can be used in upper and lower limbs rehabilitation monitoring. The advantages of using sensors based on microwave Doppler radar or infrared technologies for physiotherapy assessment are discussed. These technologies allow motion sensing at distance from monitored subject, reducing thus the discomfort produced by some wearable technologies for limbs movement assessment. The microwave radar that may be easily hidden into environment by nonmetallic parts allows remote sensing of human motion, providing information on user movements characteristics and patterns. The infrared technologies - infrared LEDs from Leap-Motion, infrared laser from Kinect depth sensor, and infrared thermography can be used for different movements' parameters evaluation. Visible for users, Leap-motion and Kinect sensors assure higher accuracy on body parts movements' detection at low computation load. These technologies are commonly used for virtual reality (VR) and augmented reality (AR) scenarios, in which the user motion patterns and the muscular activity might be analyzed. Thermography can be employed to evaluate the muscular loading. Muscular activity during movements training in physiotherapy can be estimated through skin temperature measurement before and after physical training. Issues related to the considered remote sensing technologies such as VR serious game for motor rehabilitation, signal processing and experimental results associated with microwave radar, infrared sensors and thermography for physiotherapy sensing are included in the paper.info:eu-repo/semantics/acceptedVersio

Statistical Analysis and Kinematic Assessment of Upper Limb Reaching Task in Parkinson’s Disease

The impact of neurodegenerative disorders is twofold; they affect both quality of life and healthcare expenditure. In the case of Parkinson’s disease, several strategies have been attempted to support the pharmacological treatment with rehabilitation protocols aimed at restoring motor function. In this scenario, the study of upper limb control mechanisms is particularly relevant due to the complexity of the joints involved in the movement of the arm. For these reasons, it is difficult to define proper indicators of the rehabilitation outcome. In this work, we propose a methodology to analyze and extract an ensemble of kinematic parameters from signals acquired during a complex upper limb reaching task. The methodology is tested in both healthy subjects and Parkinson’s disease patients (N = 12), and a statistical analysis is carried out to establish the value of the extracted kinematic features in distinguishing between the two groups under study. The parameters with the greatest number of significances across the submovements are duration, mean velocity, maximum velocity, maximum acceleration, and smoothness. Results allowed the identification of a subset of significant kinematic parameters that could serve as a proof-of-concept for a future definition of potential indicators of the rehabilitation outcome in Parkinson’s disease

Influence of BMI on Gait Characteristics of Young Adults: 3D Evaluation Using Inertial Sensors

Overweight/obesity is a physical condition that affects daily activities, including walking. The main purpose of this study was to identify if there is a relationship between body mass index (BMI) and gait characteristics in young adults. 12 normal weight (NW) and 10 overweight/obese (OW) individuals walked at a self-selected speed along a 14 m indoor path. H-Gait system, combining seven inertial sensors (fixed on pelvis and lower limbs), was used to record gait data. Walking speed, spatio-temporal parameters and joint kinematics in 3D were analyzed. Differences between NW and OWand correlations between BMI and gait parameters were evaluated. Conventional spatio-temporal parameters did not show statistical differences between the two groups or correlations with the BMI. However, significant results were pointed out for the joint kinematics. OW showed greater hip joint angles in frontal and transverse planes, with respect to NW. In the transverse plane, OW showed a greater knee opening angle and a shorter length of knee and ankle trajectories. Correlations were found between BMI and kinematic parameters in the frontal and transverse planes. Despite some phenomena such as soft tissue artifact and kinematics cross-talk, which have to be more deeply assessed, current results show a relationship between BMI and gait characteristics in young adults that should be looked at in osteoarthritis prevention

Inverse kinematics for upper limb compound movement estimation in exoskeleton-assisted rehabilitation

Robot-Assisted Rehabilitation (RAR) is relevant for treating patients affected by nervous system injuries (e.g., stroke and spinal cord injury) -- The accurate estimation of the joint angles of the patient limbs in RAR is critical to assess the patient improvement -- The economical prevalent method to estimate the patient posture in Exoskeleton-based RAR is to approximate the limb joint angles with the ones of the Exoskeleton -- This approximation is rough since their kinematic structures differ -- Motion capture systems (MOCAPs) can improve the estimations, at the expenses of a considerable overload of the therapy setup -- Alternatively, the Extended Inverse Kinematics Posture Estimation (EIKPE) computational method models the limb and Exoskeleton as differing parallel kinematic chains -- EIKPE has been tested with single DOFmovements of the wrist and elbow joints -- This paper presents the assessment of EIKPEwith elbow-shoulder compoundmovements (i.e., object prehension) -- Ground-truth for estimation assessment is obtained from an optical MOCAP (not intended for the treatment stage) -- The assessment shows EIKPE rendering a good numerical approximation of the actual posture during the compoundmovement execution, especially for the shoulder joint angles -- This work opens the horizon for clinical studies with patient groups, Exoskeleton models, and movements types -

Mobile Personal Health Monitoring for Automated Classification of Electrocardiogram Signals in Elderly

Mobile electrocardiogram (ECG) monitoring is an emerging area that has received increasing attention in recent years, but still real-life validation for elderly residing in low and middle-income countries is scarce. We developed a wearable ECG monitor that is integrated with a self-designed wireless sensor for ECG signal acquisition. It is used with a native purposely designed smartphone application, based on machine learning techniques, for automated classification of captured ECG beats from aged people. When tested on 100 older adults, the monitoring system discriminated normal and abnormal ECG signals with a high degree of accuracy (97%), sensitivity (100%), and specificity (96.6%). With further verification, the system could be useful for detecting cardiac abnormalities in the home environment and contribute to prevention, early diagnosis, and effective treatment of cardiovascular diseases, while keeping costs down and increasing access to healthcare services for older persons

Monitoring Walker Assistive Devices: A Novel Approach Based on Load Cells and Optical Distance Measurements

This paper presents a measurement system intended to monitor the usage of walker assistive devices. The goal is to guide the user in the correct use of the device in order to prevent risky situations and maximize comfort. Two risk indicators are defined: one related to force unbalance and the other related to motor incoordination. Force unbalance is measured by load cells attached to the walker legs, while motor incoordination is estimated by synchronizing force measurements with distance data provided by an optical sensor. The measurement system is equipped with a Bluetooth link that enables local supervision on a computer or tablet. Calibration and experimental results are included in the paper.info:eu-repo/semantics/publishedVersio

Development of a thermal model for SPS modified for the production of bioimplants

La tesi verte sulla misura della temperatura applicata a un processo industriale di sinterizzazione denominato Spark Plasma Sintering (SPS). L’SPS è un processo che consente di sinterizzare una polvere per ottenere materiali con micromorfologia e proprietà meccaniche particolari. L’attività di ricerca ha come scopo ultimo la produzione di impianti ortopedici temporanei, bioassorbibili, realizzati in magnesio e dotati di una struttura porosa predeterminata affinché le loro proprietà meccaniche siano funzionali a uno specifico sito di impianto. Per ottenere una densità e una micromorfologia adatte, è necessario che la polvere di magnesio sia trattata entro intervalli di temperatura ristretti, ma i vincoli geometrici dello stampo di sinterizzazione e la suscettibilità del sistema rispetto all’introduzione di corpi termicamente conduttivi non consentono l’uso diretto dei sensori di temperatura convenzionali. Per questo si è sviluppato e validato un modello fisico del sistema che consente di controllare il processo in modo accurato facendo uso solamente di misure di prossimità. Il modello sviluppato è stato sfruttato per sviluppare e confrontare soluzioni innovative per il processo di sinterizzazione. La tesi descrive infatti una configurazione innovativa per il processo, che fa uso di uno stampo di allumina in sostituzione di quello convenzionale di grafite, e questa configurazione garantisce un maggiore controllo delle proprietà finali del materiale perché permette di conoscere meglio la distribuzione di temperatura nello stampo

Interaction Modalities Used on Serious Games for Upper Limb Rehabilitation: A Systematic Review

This systematic review aims to analyze the state-of-the-art regarding interaction modalities used on serious games for upper limb rehabilitation. A systematic search was performed in IEEE Xplore and Web of Science databases. PRISMA and QualSyst protocols were used to filter and assess the articles. Articles must meet the following inclusion criteria: they must be written in English; be at least four pages in length; use or develop serious games; focus on upper limb rehabilitation; and be published between 2007 and 2017. Of 121 articles initially retrieved, 33 articles met the inclusion criteria. Three interaction modalities were found: vision systems (42.4%), complementary vision systems (30.3%), and no-vision systems (27.2%). Vision systems and no-vision systems obtained a similar mean QualSyst (86%) followed by complementary vision systems (85.7%). Almost half of the studies used vision systems as the interaction modality (42.4%) and used the Kinect sensor to collect the body movements (48.48%). The shoulder was the most treated body part in the studies (19%). A key limitation of vision systems and complementary vision systems is that their device performances might be affected by lighting conditions. A main limitation of the no-vision systems is that the range-of-motion in angles of the body movement might not be measured accurately. Due to a limited number of studies, fruitful areas for further research could be the following: serious games focused on finger rehabilitation and trauma injuries, game difficulty adaptation based on user's muscle strength and posture, and multisensor data fusion on interaction modalities