Smart Wheelchairs - A literature review

This article presents a summary of current state of smart wheelchairs. An assistive technology known as wheelchair is used to deal with loss of mobility for the patients who are not able to walk normally due to some injury or some other age related walking disabilities (permanent or under treatment). There is a vast development in the field of wheelchairs. Researchers are going on to develop reliable, low cost and easy to use devices. Out of all the methodologies, HCI (Human Computer Interface) and HMI (Human Machine Interface) are the latest and most effective techniques [5]. In user interface systems both bio-signals and non bio-signals are used as a medium of control. Bio-signal based devices mainly use bio-signals like EEG, EOG or EMG as control signals. The advantage of using bio-signal approach is that when patients become completely paralyzed, the only resource available to them then is bio-signals. Non bio-signal based devices provide 100% accuracy and require less training for patients but the usage of these devices is limited to patients with partial or complete flexibility in their body parts. KEYWORDSHCI (Human Computer Interface), HMI (Human Machine Interface), Wheelchair I.INTRODUCTION A handicapped person with locomotive disabilities needs a wheelchair to perform functions that require him or her to move around. He can do so manually by pushing the wheelchair with his hands. However, many individuals have weak upper limbs or find the manual mode of operating too tiring. Hence, it is desirable to provide them with a motorized smart wheelchair that can be controlled by bio-signal & non bio-signal approach. Since the motorized wheelchair can move at a fair speed with minimum efforts. There are different types of wheelchairs available now days which are discussed below. A. Manual Wheelchairs These are the type of devices that help a person to move him without any assistance of battery. There are three types of manual wheelchairs namely self-propelled, attendant propelled, and wheelbase. A single-arm drive enables the user to turn either left or right while the two-armed drive enables user to move forward or backward on a straight line. Another type of wheelchair commonly used is a lever-drive wheelchair. This type of chair enables the user to move forward by pumping the lever back and forth [1]. B. Electric Wheelchairs A power chair can be used by someone who hasn’t got the dexterity or mobility, perhaps, to drive a mobility scooter due to arm, hand, shoulder or more general disabling conditions, and do not have the leg strength to propel a manual chair with their feet. Powered wheelchair can offer various powered functions such as tilt, recline, leg elevation, seat elevation, and others useful or necessary to health function [1]. C. Standing Wheelchairs ‘Redman power chair’, it is the world’s highest quality standing wheelchair. People with spinal cord injury can reap the health benefits of standing wheelchair. Physical benefits of standing wheelchairs are  Decrease urinary tract infection problem  Improver blood circulation around the body  Standing exercise greatly improve bowl function  Wheelchair helps distribute your weight and improve healing bed sores  Decrease the amount of muscle stiffness  Increase bone density International Journal of Innovative and Emerging Research in Engineering Volume 3, Issue 2, 2016 87  Increase cognition, well being and independence [2] D. Pediatric Wheelchair These types of wheelchair provide a key-enabling technology to young children who would be unable to navigate independently in their environment. Standard powered wheelchairs are still heavily dependent on the cognitive capabilities of users. Unfortunately, this excludes disabled users who lack the required problem-solving and spatial skills, particularly young children. For these children to be denied powered mobility is a crucial set-back; exploration is important for their cognitive, emotional and psychosocial development [3]. E. STAIR CLIMBING WHEEL CHAIR The stair-climbing wheelchair exists at present can be grouped into 3 categories: continuous stair climbing wheelchair, intermittent-stair climbing wheelchair and auxiliary stair climbing wheelchair. Continuous stair climbing wheelchair has only one set of supporting device, the wheelchair relies on this supporting device for continuous motions. In Intermittent stair climbing wheelchair the process of climbing stairs of is similar to the people climbing up and down stairs, it is also called walking stair climbing wheelchair. Intermittent stair climbing wheelchair is one of the supporting devices that elevate the wheelchair and other set of support system. In auxiliary stair climbing wheelchair, the attachments rely on another device installed on the wheelchair and it needs assistance to help realize the function of climbing stairs. Stair lift requires wide stair way which is very expensive [4]. II.VARIOUS TECHNIQUE USED IN WHEELCHAIR CONTROL There is a vast development in the field of wheelchairs. Out of all the methodologies, HCI (Human Computer Interface) and HMI (Human Machine Interface) are the latest and most effective techniques. In user interface systems both bio-signals and non bio-signals are used as a medium of control. Bio-signal based devices mainly use bio-signals like EEG, EOG or EMG as control signals. The bio-signal based approach is used for completely paralyzed patients who can only use their bio-signals as the only resource to control [5]. A.EEG based The Electroencephalography (EEG) records electrical brain signals from the scalp, where the brain signal originates from postsynaptic potentials, aggregates at the cortex, and transfers through the skull to the scalp. BCI is a device that extracts EEG data from brain and converts it into device control commands using signal processing techniques. EEG techniques are non-invasive and low cost. However, it brings great challenges to signal processing and pattern recognition, since it has relatively poor signal-to-noise ratio and limited topographical resolution and frequency range [6, 7, and 8]. B. EMG based EMG measures electrical currents that are generated in muscles during its contraction. A muscle fiber contracts when it receives an action potential. The EMG observed is the sum of all the action potentials that occur around the electrode site. In almost all cases, muscle contraction causes an increase in the overall amplitude of the EMG. EMG signals can be used for a variety of applications including clinical applications, HCI and interactive computer gaming. They are easy to acquire and of relatively high magnitude than other bio-signals. On the other hand, EMG signals are easily susceptible to noise. EMG signals contain complicated types of noise that are caused by inherent equipment noise, electromagnetic radiation, motion artifacts, and the interaction of different tissues. Hence preprocessing is necessary to filter unwanted noise in EMG. The EMG signals also have different signatures depending on age, muscle development, motor unit paths, skin fat layer, and gesture styles. The external appearances of two individuals’ gestures might look identical, but the characteristic EMG signals are different [9]. C. EOG based EOG based technique are very useful for persons who born with any congenital brain disorder or for those who are suffer from severe brain trauma. EOG signals records the potential difference between the retina and cornea of the eye. When the eyes are rolled upward or downward, positive or negative pulses are generated. As the rolling angle increases, amplitude of pulse also increases and the width of the pulse is in directly proportional to the eyeball rolling process [10, 11]. C. Non Bio-signal based Non bio-signal based devices provide 100% accuracy and require less training for patients. In general, non biosignal based techniques which make use of joystick control, sip-n-puff control, tongue control, Touch screen controlled, Voice actuated, head movement tracking etc [5]. D. Sip-n-Puff Technology International Journal of Innovative and Emerging Research in Engineering Volume 3, Issue 2, 2016 88 In this method using air presser to generates control signals by sipping (inhaling) or puffing (exhaling) in a tube. This technology generates four control signals for motorized wheelchair which are initial hard puffs, hard sip, initial hard sip, and hard puff. It is mostly used for quadriplegics having injury in their spinal cord or people with ALS. But this is not good for individual with week breathing. E. Head Orientation Tracking Technique Here in this method, head movements are transformed into cursor movements on the screen. Cursor movements are proportional to head movements. Head movements are calculated by different methods like accelerometer placed in a patient’s cap or by capturing video of head movements. But the problem with this technique is that differentially able people of certain categories such as cerebral palsy patients cannot even move their head comfortably. Another problem of this technique is that forehead continuously needs to face the camera [12, 13]. F. Chin Control Technique In this technique chin is put in cup shape joystick and is usually controlled by neck movements (flexion, extension, and rotation). The major problem that arises in this mode of control is the need for constant pressure in chin cup [14]. G. Eye Tracking Technique In this technique wheelchair is controlled by an optical type eye tracking system (screen based system). Camera is used to continuously track the features of eye. There after a calibration algorithm is used to find the direction of eye gaze in real time. Than according to gazed position, screen movement control signals are calculated to control the wheelchair [15, 16 and 17]. H. Tongue Controlled This technology is based on Faraday’s law. Permanent magnet is used here and is attached to tongue. As the tongue move in air core induction coil, the inductance is changed. A Hall Effect sensor is placed in the stud of tongue. Hall Effect sensor is a transducer that varies its output in response to change in magnetic field. The movement of tongue is traced by of Hall Effect sensor. Thereafter, the Output signals are collected that provide continuous real time analog output [18]. I. Image Processing Algorithm Here, webcam is used for capturing image input from the finger of user. After that we use an image processing algorithm (image blurring, RGB to HSV conversion, HSV thresholding) that helps in finger detection. According to direction of finger, wheelchair moves in left-right or in front back direction [19]. J. Brain Actuated Wheelchair using Brain Wave Sensor There is billions of interconnected neuron in human brain. The way, neurons are connected to each other depicts the various thought processes and emotional states. This pattern of neurons connection keeps on changing according to the human thought & process different electrical signals. For sensing these electrical signals, brain wave sensor is used that convert the data into packetswhich are transmitted through bluetooth medium. Level analyzer unit (LAU) is used to receive raw data. The extraction and processing of the signal is done using Matlab platform. The control commands are transmitted to the robotic module to process. With this entire system, any robot can be moved according to the human thoughts and it can be turned by blink muscle contraction. By using this brainwave concept executed in wheelchair the handicap can easily controls wheel chair [20]. K. Accelerometer Based In accelerometer based wheelchair, we have an acceleration sensor that is also known as tilt sensor. When we tilt the object, the values registered by sensor are changed and these values are given to microcontroller. Depending on the direction of the tilt, microcontroller controls the wheelchair directions as LEFT, RIGHT, FRONT and BACK [21]. L. Based on Deictic Approach The deictic approach uses the vision of the environment as a control interface. This vision must be as close as possible to the perception of the user so that the interface is intuitive and therefore easy to use. To move, the user specifies the location within the environment he wants to go to by pointing at it on the interface. Then the wheelchair will move automatically to that position. As the command is given from time to time, it does not require much effort from the user [22]. M.Touch screen controlled The mode of input control to the wheelchair is touch screen. When user wants to change the direction, the touch screen sensor is modeled by pressing finger against the various quadrants on the touch screen, which has different values for different direction [23]. International Journal of Innovative and Emerging Research in Engineering Volume 3, Issue 2, 2016 89 N. Voice actuated In this technique user speak in microphone and the voice recognition system compares the voice command with pre-stored memory and generates a control signal to control the movements of wheels [24, 25 and 26]. III. DRAW BACKS OF PRESENTLY AVAILABLE WHEELCHAIRS Most significant technical issue in the currently available wheelchairs is cost versus accuracy. Unavailability of wheelchairs for particular disabilitiy is also a considerable issue. Also, the present systems are unable to monitor the surrounding conditions and the health condition of the patient. There is also no wheelchair available till date for the bed lying patient. No wheelchair available for mentally challenged people also. Above all the other important aspect to consider is the physical barrier that place additional requirement on strength and durability of wheelchairs. IV.FUTURE SCOPE OF WHEELCHAIRS Proposed method is controlling of the wheelchair by the thought process. In this technology person can control the motion of the same by just thinking. This vehicle can be modeled in such a way that it can be easily turned into a semi sleeper mode in order to make the patient feel more comfortable and thereby reducing the continuous one mode sitting problem. Other already invented methods in wheelchair can also be incorporated with this [3]. Like step climbing wheelchair and inter communication between devices-which is just an upcoming project trying to be implemented on road vehicles. The communication aid with these wheelchairs will help the deaf and dumb to communicate with each other’s too [3]. These all are the (much more can be thought of) proposed for the Future scopes of smart wheelchairs. V. CONCLUSIONThis paper presents a summary of current state-of-the-art smart wheelchairs. Various techniques are available to operate andcontrol the wheel mechanism of wheelchair. Some of operating techniques of wheelchairs have been explained here. Thisinformation is gathered to promote awareness of status of existing types of smart powered wheelchair so that the improvementcan be incorporated into it. REFERENCES[1] Arvind Prasad, Snehal Shah, PriyankaRuparelia, AshishSawant,”Powered Wheelchairs”, International Journal OfScientific & Technology Research ,Vol. 2, Issue 11, pp. 162-165, November 2013[2] Julianna Arva, MS, ATP,Ginny Paleg, PT, Michelle Lange, OTR, ABDA, ATP, Jenny Lieberman, MSOTR/L,ATP,4Mark Schmeler, PhD, OTR/L, ATP, Brad Dicianno, MD,6Mike Babinec, OTR/L, ABDA, ATP,and LaurenRosen, PT, MPT, ATP,” RESNA Position on the Application of Wheelchair Standing Devices”, Taylor & Francis,Vol. 21, pp. 161-168, 2009[3] Nirmal T M,” Wheelchair for Physically and Mentally Disabled Persons”, International Journal of Electrical andElectronics Research, Vol. 2, Issue 2, pp. 112-118, April June 2014,[4] LinZhang, X-Feihong,” An optimazationdesign of stair climbing wheelchair”, master of technology, department ofmechanical engg. Bleking institute of technology Karlskrona, Sweden 2012[5] Jobin Jose, “Development of EOG Based Human Machine Interface Control System for Motorized Wheelchair”,Master of Technology, Department of Biotechnology and Medical Engineering National Institute of TechnologyRourkela, Odisha, 769 008, India, June 2013[6] Murali Krishnan, Muralindran Mariappan,” EEG-Based Brain-Machine Interface (BMI) for Controlling MobileRobots: The Trend of Prior Studies”, IJCSEE, Vol. 3, pp.159-165, Issue 2, 2015.[7] Vijay Khare, Jayashree Santhosh, Sneh Anand, Manvir Bhatia,” Brain Computer Interface Based Real Time Controlof Wheelchair Using Electroencephalogram”, International Journal of Soft Computing and Engineering (IJSCE), Vol.1, Issue 5, pp. 41-45, November 2011[8] Tom Carlson, Jose Del R. Millan,” Brain–Controlled Wheelchairs: A Robotic Architecture”, IEEE Robotics andAutomation Magazine, Vol. 20(1), pp. 65 – 73, March 2013[9] Sathishbalaji L, Bhakkiyalakshmi R,” Electric Wheelchair Controlled by EMG Signals with Obstacle Detection”,IJEDR, Vol. 2, Issue 2, pp. 1409-1412, 2014[10] Yathunanthan, S. chandrasena, L.U.R, umakanthan, A., Vasuki, V,”Controlling a wheelchair using EOG Signal”,IEEE, PP. 283-288, Dec. 2015[11] Jobby K. Chacko, Deepu Oommen, Kevin K. Mathew, Noble Sunny, N. Babu,” Microcontroller Based EOG GuidedWheelchair”, International Journal of Medical, Health, Biomedical, Bioengineering and PharmaceuticalEngineering, Vol. 7(11), pp.423-426, 2013[12] Aleksandar Pajkanović, Branko Dokić,” Wheelchair Control by Head Motion”, Serbian Journal of ElectricalEngineering, Vol. 10(1), pp. 135-151 February 2013,[13] Manju Davy, R.Deepa,” Hardware Implementation Based On Head Movement Using Accelerometer Sensor”, Int.Journal of Applied Sciences and Engineering Research, Vol. 3, Issue 1, pp.17-21, 2014 International Journal of Innovative and Emerging Research in Engineering Volume 3, Issue 2, 2016 90[14] Songfeng Guo , Cooper, R.A., Boninger, M.L., Kwarciak, A.,” Development of power wheelchair chin-operated force-sensing joystick”, IEEE, Vol.3, pp.2373-2374, Oct 2002[15] Chern-Sheng Lin, Chien-Waho, Wen-Chen, Chuang-Chien Chiu, Mav-Shiun Yeh,” Powered wheelchair controlledby eye tracking system”, Optica Applicata, Vol. XXXVI, no.2-3, pp. 401-412, 2006[16] Poonam S. Gajwani, Sharda A. Chhabria,” Eye motion tracking for wheelchair control”, International Journal ofInformation Technology and Knowledge Management, Vol. 2, No. 2, pp. 185-187, July-December 2010[17] Gunda Gautam, Gunda Sumanth, Karthikeyan K C, Shyam Sundar, D.Venkataraman,” Eye Movement BasedElectronic Wheel Chair For Physically Challenged Persons”, International Journal Of Scientific & TechnologyResearch, Vol. 3, Issue 2, pp. 206-212, February 2014[18] A. Ruíz-Serranoa , R. Posada-Gómeza , A. Martínez Sibajaa , G. Aguila Rodrígueza , B.E. Gonzalez-Sancheza , O.O.Sandoval-Gonzaleza,” Development of a dual control system applied to a smart wheelchair, using magnetic and speechcontrol”, Iberoamerican Conference on Electronics Engineering and Computer Science ELSEVIER, Vol. 7, pp. 158– 165, 2013[19] Chhaya.G.Patil1,Sayali.K.Gharge, Sonal.V.Modhave, Y.S.Angal,” Design of wheelchair using finger operation withimage processing algorithms”, (IJRET) International Journal of Research in Engineering and Technology, Vol. 03Issue 02, pp. 232-237, Feb-2014,[20] Aswathy M,” Brain actuated wheelchair using brain wave sensor”, International Journal of Engineering, Businessand Enterprise Applications (IJEBEA), Vol. 11(1), pp. 78-82, December 2014-February 2015[21] Rakhi A. Kalantri, D.K. Chitre,” Automatic Wheelchair using Gesture Recognition”, International Journal ofEngineering and Innovative Technology (IJEIT,) Vol. 2, Issue 9, pp. 216-218, March 2013[22] F. Leishman, O. Horn, G. Bourhis,” Smart wheelchair control through a deictic approach”, Robotics and AutonomousSystems ELSEVIER, Vol. 58, pp. 1149–1158, 2010[23] Vasundhara G. Posugade, Komal K. Shedge, Chaitali S. Tikhe,”Touch-screen based wheelchair system”,International Journal of Engineering Research and Applications (IJERA), Vol. 2, Issue 2, pp.1245-1248, Mar-Apr2012[24] Aruna, C.Dhivya Parameswari, A. ; Malini, M. ; Gopu, G.” Voice recognition and touch screen control based wheelchair for paraplegic persons”, IEEE, pp. 1-5, 6-8 March 2014[25] Ms. S. D. Suryawanshi Mr. J. S. Chitode Ms. S. S. Pethakar,” Voice Operated Intelligent Wheelchair”, InternationalJournal of Advanced Research in Computer Science and Software Engineering, Vol. 3, Issue 5, pp. 487-490, May2013[26] Anoop.K.J1 , Inbaezhilan2 , Sathish raj3 , Ramaseenivasan4 , CholaPandian5,” Designing and Modeling of VoiceControlled Wheel Chair Incorporated with Home Automation”, International Journal of Advanced Research inElectrical, Electronics and Instrumentation Engineering, Vol. 3, Issue 2, pp. 53-60, April 2014