Effectiveness of Morse Code as an Alternative Control Method for Powered Wheelchair Navigation

We applied Morse code as an alternative input method for powered wheelchair navigation to improve driving efficiency for individuals with physical disabilities. In lab trials performed by four testers, it demonstrated significant improvement in driving efficiency by reducing the driving time, compared to traditional single switch wheelchair navigation

Intelligent single switch wheelchair navigation

We have developed an intelligent single switch scanning interface and wheelchair navigation assistance system, called intelligent single switch wheelchair navigation (ISSWN), to improve driving safety, comfort and efficiency for individuals who rely on single switch scanning as a control method. ISSWN combines a standard powered wheelchair with a laser rangefinder, a single switch scanning interface and a computer. It provides the user with context sensitive and task specific scanning options that reduce driving effort based on an interpretation of sensor data together with user input. Trials performed by 9 able-bodied participants showed that the system significantly improved driving safety and efficiency in a navigation task by significantly reducing the number of switch presses to 43.5% of traditional single switch wheelchair navigation (p < 0.001). All participants made a significant improvement (39.1%; p < 0.001) in completion time after only two trials. Implications for Rehabilitation Intelligent navigation algorithm helps investigators develop smart wheelchair technology that may ultimately provide independent mobility to a segment of the population that currently finds it difficult or impossible to operate a conventional wheelchair. intelligent single switch wheelchair navigation improves the driving safety, comfort, and efficiency for individuals who rely on single switch scanning as a wheelchair control method by significantly reducing the number of switch presses and completion time. © 2012 Informa UK, Ltd

Overcoming barriers and increasing independence: service robots for elderly and disabled people

This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control

Instrumented wheelchair operates based on surface electromyography (sEMG) is one of alternative to assist impairment person for mobility. SEMG is chosen due to good in accuracy and easier preparation to place the electrodes. Motor neuron transmit electrical potential to muscle fibre to perform isometric, concentric or eccentric contraction. These electrical changes that is called Motor Unit Action Potential (MUAP) can be acquired and amplified by electrodes located on targeted muscles changes can be recorded and analysed using sEMG devices. But, sEMG device cost up to USD 2,100 for a sEMG data acquisition device that available on market is one of the drawback to be used by impairment person that most of them has financial problem due to unable to work like before. In addition, it is a closed source system that cannot be modified to improve the accuracy and adding more features. Open source system such as Arduino has limitation of specifications that makes able to apply nonpattern recognition control methods which is simpler and easier compared to pattern recognition. However, classification accuracy is lower than pattern recognition and it cannot be applied to higher number participants from different background and gender. This research aims are to develop an open-source Arduino based sEMG data acquisition device by formulating hybrid automata algorithm to differentiate MUAP activity during wheelchair propulsion. Addition of hybrid automata algorithm to run pattern and non-pattern recognition based control methods is an advantage to increase accuracy in differentiating forward stroke or hand return activity. Electrodes are placed on Biceps (BIC), Triceps (TRI), Extensor (EXT), Flexor (FIX) and MUAP activity recorded for 30 healthy persons. Then, experiment result was validated with simulation result using OpenSim biomedical modelling software. Mean, standard deviation (SD), confidence interval (CI) and maximum point different (MPD) of MUAP were calculated and to be used as thresholds for non-pattern recognition control method in method selection experiment. Meanwhile, pattern recognition is using Probability Density Function (PDF) to determine MUAP according to type of activities. Total of ten control methods determined from population and individual data were tested against another 10 healthy persons to evaluate the algorithm performance. Assessment of each control method done by misclassification matrix looking at True Positive (TP) and False Negative (FN) of power assist system activation period. Developed sEMG data acquisition device that is operated by Arduino MEGA 2560 and Myoware muscle sensors with sampling rate of above 400Hz successfully recorded MUAP from four arm muscles. Furthermore, 2.5 ms of average data latency for device to record, analyse, validate and creating commands to activate the power assist system. Data obtained from the device shows that most active muscle during wheelchair propulsion is TRI, followed by BIC and matched to OpenSim simulation result. In method selection experiment, 96.28% of average accuracy was achieved and different control methods were selected by misclassification matrix for each of persons. This method would be a control method to activate power assist system and selected based on conditions set in the algorithm. These findings indicated that open source Arduino board is capable of running real time pattern, non-pattern recognition based control methods by producing classification accuracy up to 99.48% even though it is known as just a microcontroller that has limitation to run complex classifiers. At the same time, a device that cost less than USD200 has 400Hz of sampling rate is as good as closed source device that is come with expensive price tag to own it. Based on algorithm evaluation, it shows that one control method couldn’t fit to all persons as per proven in method selection experiment. Different person has different control method that suit them the most. Lastly, BIC and TRI can be reference muscles to activate assistive device in instrumented wheelchair that is using propulsion as indication

Autonomous wheelchair with a smart driving mode and a Wi-Fi positioning system

Wheelchairs are an important aid that enhances the mobility of people with several types of disabilities. Therefore, there has been considerable research and development on wheelchairs to meet the needs of the disabled. Since the early manual wheelchairs to their more recent electric powered counterparts, advancements have focused on improving autonomy in mobility. Other developments, such as Internet advancements, have developed the concept of the Internet of Things (IoT). This is a promising area that has been studied to enhance the independent operation of the electrical wheelchairs by enabling autonomous navigation and obstacle avoidance. This dissertation describes shortly the design of an autonomous wheelchair of the IPL/IT (Instituto Politécnico de Leiria/Instituto de Telecomunicações) with smart driving features for persons with visual impairments. The objective is to improve the prototype of an intelligent wheelchair. The first prototype of the wheelchair was built to control it by voice, ocular movements, and GPS (Global Positioning System). Furthermore, the IPL/IT wheelchair acquired a remote control feature which could prove useful for persons with low levels of visual impairment. This tele-assistance mode will be helpful to the family of the wheelchair user or, simply, to a health care assistant. Indoor and outdoor positioning systems, with printed directional Wi-Fi antennas, have been deployed to enable a precise location of our wheelchair. The underlying framework for the wheelchair system is the IPL/IT low cost autonomous wheelchair prototype that is based on IoT technology for improved affordability