Development of Rehabilitation System (RehabGame) through Monte-Carlo Tree Search Algorithm using Kinect and Myo Sensor Interface

Artificial and Computational Intelligence in computer games play an important role that could simulate various aspects of real life problems. Development of artificial intelligence techniques in real time decision-making games can provide a platform for the examination of tree search algorithms. In this paper, we present a rehabilitation system known as RehabGame in which the Monte-Carlo Tree Search algorithm is used. The objective of the game is to combat the physical impairment of stroke/ brain injury casualties in order to improve upper limb movement. Through the process of a real-time rehabilitation game, the player decides on paths that could be taken by her/his upper limb in order to reach virtual goal objects. The system has the capability of adjusting the difficulty level to the player0 s ability by learning from the movements made and generating further subsequent objects. The game collects orientation, muscle and joint activity data and utilizes them to make decisions on game progression. Limb movements are stored in the search tree which is used to determine the location of new target virtual fruit objects by accessing the data saved in the background from different game plays. It monitors the enactment of the muscles strain and stress through the Myo armband sensor and provides the next step required for the rehabilitation purpose. The results from two samples show the effectiveness of the MonteCarlo Tree Search in the RehabGame by being able to build a coherent hand motion. It progresses from highly achievable paths to the less achievable ones, thus configuring and personalizing the rehabilitation process

Splitting tensile and pullout behavior of synthetic wastes as fiber-reinforced concrete

Plastic bottles and waste wires are the most commonly discarded synthetic wastes that contribute to environmental pollution. Polyethylene terephthalate (PET) bottles act as one of the contributors to environmental pollution. One solution to environmental pollution includes recycling plastic bottle wastes as synthetic fibers and incorporating them into concrete. Therefore, pullout strengths of synthetic fibers in a concrete matrix should be investigated by conducting splitting tensile and pullout tests. Experiments of the present study used fibers from ring-shaped PET bottles with widths of 5 and 10 mm. Irregularly shaped PET bottles with 10–15 mm size, waste wires measuring 55 mm in length, and manufactured synthetic macro-fibers were also used in comparative analysis. Results indicate that an increase in fiber volume improves tensile strength of concrete. Incorporation of high-volume fiber with concrete results in a substantial amount of fibers bridging and crossing fractured sections, thereby activating failure resistance mechanisms. In comparison with irregularly shaped PET and waste wire fibers, ring-shaped fibers performed better as they are mainly designed to activate fiber yielding instead of fiber pullout. The load energy required to debond fibers and the concrete matrix was high when the surface contact area was large in comparison with that when a small surface contact area was considered. Fibers with small surface contact area easily slip under tensile stress. Thus, the surface contact area of fibers with concrete matrix allows good frictional resistance against pullout or tensile loa

Real estate investment as a panacea for economic instability in Nigeria: evidence from northeastern states of Nigeria

Real estate investment is an emerging business in many countries of the world. Real estate investment was thoroughly investigated to come up with solution faced by the transaction of land and building. Real estate investment is strictly related to the housing price. It has been pointed out by many researchers that the housing price is affected by many factors, such as interest rate, land supply, government policies and inflation rate. The research highlighted most important aspects of the outcomes. An increase in international real estate capital flows could foster increasing demand for stronger institutions across a global real estate market. The method adopted in this research was quantitative through which 100 questionnaires were developed and distributed within the study area (Bauchi, Gombe, Adamawa and Yobe States). The simple percentage was used to analyzed the data collected. The research is exploratory in nature; hence, a non-probability purposive sampling technique was used for the study. The finding of the research vindicated that real estate investment has a significant role in sharpening the economy of the region, and also the findings revealed that real estate investment opportunity is huge. And again for suggested that housing provision cannot be realized only by private individual excerpts through government intervention. The study concludes that real estate investment, if explore it will create a reliable return to the investment owners, the benefits that can be derived from real estate investment, has been revealed by this study. The study also highlighted that private developers are key important for real estate investment in Nigeria. The conclusion drawn by this research shows that real estate investment has a capacity of transforming economic hardship in the country

A comparison of machine learning classifiers for smartphone-based gait analysis

This paper proposes a reliable monitoring scheme that can assist medical specialists in watching over the patient's condition. Although several technologies are traditionally used to acquire motion data of patients, the high costs as well as the large spaces they require make them difficult to be applied in a home context for rehabilitation. A reliable patient monitoring technique, which can automatically record and classify patient movements, is mandatory for a telemedicine protocol. In this paper, a comparison of several state-of-the-art machine learning classifiers is proposed, where stride data are collected by using a smartphone. The main goal is to identify a robust methodology able to assure a suited classification of gait movements, in order to allow the monitoring of patients in time as well as to discriminate among a pathological and physiological gait. Additionally, the advantages of smartphones of being compact, cost-effective and relatively easy to operate make these devices particularly suited for home-based rehabilitation programs. Graphical Abstract. This paper proposes a reliable monitoring scheme that can assist medical specialists in watching over the patient's condition. Although several technologies are traditionally used to acquire motion data of patients, the high costs as well as the large spaces they require make them difficult to be applied in a home context for rehabilitation. A reliable patient monitoring technique, which can automatically record and classify patient movements, is mandatory for a telemedicine protocol. In this paper, a comparison of several state-of-the-art machine learning classifiers is proposed, where stride data are collected and processed by using a smartphone(see figure). The main goal is to identify a robust methodology able to assure a suited classification of gait movements, in order to allow the monitoring of patients in time as well as to discriminate among a pathological and physiological gait. Additionally, the advantages of smartphones of being compact, cost-effective and relatively easy to operate make these devices particularly suited for home-based rehabilitation programs

Implementation and validation of a stride length estimation algorithm, using a single basic inertial sensor on healthy subjects and patients suffering from Parkinson’s disease

As low cost and highly portable sensors, inertial measurements units (IMU) have become increasingly used in gait analysis, embodying an efficient alternative to motion capture systems. Meanwhile, being able to compute reliably accurate spatial gait parameters using few sensors remains a relatively complex problematic. Providing a clinical oriented solution, our study presents a gyrometer and accelerometer based algorithm for stride length estimation. Compared to most of the numerous existing works where only an averaged stride length is computed from several IMU, or where the use of the magnetometer is incompatible with everyday use, our challenge here has been to extract each individual stride length in an easy-to-use algorithm requiring only one inertial sensor attached to the subject shank. Our results were validated on healthy subjects and patients suffering from Parkinson’s disease (PD). Estimated stride lengths were compared to GAITRite© walkway system data: the mean error over all the strides was less than 6% for healthy group and 10.3% for PD group. This method provides a reliable portable solution for monitoring the instantaneous stride length and opens the way to promising applications

Wearables for independent living in older adults: Gait and falls

Solutions are needed to satisfy care demands of older adults to live independently. Wearable technology (wearables) is one approach that offers a viable means for ubiquitous, sustainable and scalable monitoring of the health of older adults in habitual free-living environments. Gait has been presented as a relevant (bio)marker in ageing and pathological studies, with objective assessment achievable by inertial-based wearables. Commercial wearables have struggled to provide accurate analytics and have been limited by non-clinically oriented gait outcomes. Moreover, some research-grade wearables also fail to provide transparent functionality due to limitations in proprietary software. Innovation within this field is often sporadic, with large heterogeneity of wearable types and algorithms for gait outcomes leading to a lack of pragmatic use. This review provides a summary of the recent literature on gait assessment through the use of wearables, focusing on the need for an algorithm fusion approach to measurement, culminating in the ability to better detect and classify falls. A brief presentation of wearables in one pathological group is presented, identifying appropriate work for researchers in other cohorts to utilise. Suggestions for how this domain needs to progress are also summarised

Developing innovative crutch using IDeS (industrial design structure) methodology

The present study wants to bring to light a new type of crutch designed for a chronic patient with perennial limited mobility, who must use this support every time a move is needed. The main purpose of the project consists in recommending a correct use of the crutch through technology, limiting the damage normally caused by a bad use of crutches and giving a support both for the patient and for the doctor. All of the features of the crutches were defined through relationship matrices and a benchmarking, which helped us for defining the requirements; other important features were defined, taking a look to the technological progresses applied to new, patented crutches. The result is a sensorized crutch, functional and oriented to meet the user's needs in order to prevent an incorrect use of the support avoiding the growth of other pains

ReHabgame: A non-immersive virtual reality rehabilitation system with applications in neuroscience

This paper proposes the use of a non-immersive virtual reality rehabilitation system ”ReHabgame” developed using Microsoft KinectT M and the ThalmicT M Labs Myo gesture control armband. The ReHabgame was developed based on two third-person video games that provide a feasible possibility of assessing postural control and functional reach tests. It accurately quantifies specific postural control mechanisms including timed standing balance, functional reach tests using real-time anatomical landmark orientation, joint velocity, and acceleration while end trajectories were calculated using an inverse kinematics algorithm. The game was designed to help patients with neurological impairment to be subjected to physiotherapy activity and practice postures of daily activities. The subjective experience of the ReHabgame was studied through the development of an Engagement Questionnaire (EQ) for qualitative, quantitative and Rasch model. The Monte-Carlo Tree Search (MCTS) and Random object (ROG) generator algorithms were used to adapt the physical and gameplay intensity in the ReHabgame based on the Motor Assessment Scale (MAS) and Hierarchical Scoring System (HSS). Rasch analysis was conducted to assess the psychometric characteristics of the ReHabgame and to identify if these are any misfitting items in the game. Rasch rating scale model (RSM) was used to assess the engagement of players in the ReHabgame and evaluate the effectiveness and attractiveness of the game. The results showed that the scales assessing the rehabilitation process met Rasch expectations of reliability, and unidimensionality. Infit and outfit mean squares values are in the range of (0.68 − 1.52) for all considered 16 items. The Root Mean Square Residual (RMSR) and the person separation reliability were acceptable. The item/person map showed that the persons and items were clustered symmetrically