tend to disable normal balance and movement of the

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1 ROBOTIC WHEELE WALKER FOR THE AGE USING SPEECH RECOGNITION Archibald anquah-amoah 1, aniel Amiteye 2, Bassey Eno Basiono 3, Akyampon-Sakyi Yaw epartment of Biomedical Engineering, All Nations University, Koforidua Ghana ABSTRACT Walking is most often the primary form of exercise for the aged and most of them require walking frames for this activity due to ailments like arthritis and osteoporosis, commonly associated with the aged, which tend to disable normal balance and movement of the body when walking. There are risks of falling associated with the use of walkers mostly due to the tendency of the walker rolling too far forward, thereby causing the user to lose balance and also, the inability of the user to squeeze the hand levers to activate the brakes. These risks increase with age and since walkers are often used by frail and vulnerable older adults, falling, for them, can have serious consequences on their health. For this reason, we designed a walking frame incorporating both robotic technology and speech recognition, which enables the user control the walker s navigation and speed using speech commands. The materials used were wood, EZ-B v3 Bluetooth Robot Controller, continuous rotation servos, 6 AA batteries and peripheral cables for connections. The EZ-B v3 Bluetooth Robot Controllerwas configured with different speech commands using the EZ-Builder Robot Control Software. Speech recognition tests were carried out on the robotic walker in both quiet and noisy environments. There was a 92% positive response from the walker when the test was carried out in a quiet environment, while that of the noisy environment recorded a 78% positive response. A control test using sounds was also carried out to which the walker s response was 100% negative. These results show that the robotic walker responds to only speech commands and that noise interferes with the speech which reduces the walker s effectiveness. 1. INTROUCTION Walking is very beneficial to the health. It is an effective way to lower blood sugar, reduce body fat, lower blood pressure, and improve bone density. It can also significantly reduce the risk of heart attack or stroke. For the aged, walking is often their primary and, in most cases, only form of exercise. As such, devices that provide mobility assistance are critical for the health and well-being of such individuals. Also, most ailments associated with aging, such as arthritis and osteoporosis, tend to disable normal balance and movement of the body when walking. Consequently, elderly patients may require walking frames to move around safely [1]. A walking frame or walker is a tool for disabled or elderly people who need additional support to maintain balance or stability while walking [2].It is also commonly used as part of the gait rehabilitation process for a variety of clinical conditions.walkers come in different designs. Standard walking frames require that the user have enough strength in the upper body to safely pick up the walker, place it in front of the body and step towards it. Some designs have wheels on all four or just two legs, which help to conserve energy as the walker does not have to be lifted at every step.this makes walking much more comfortable and less strenuous. Research has shown that although walking frames are helpful,easier to use and provide more stability,they still have some limitations such as; the tendency for the walker to roll too far forward thereby causing the user to lose his/her balance, and the inability there is a risk of falling while using it, and this risk increases with age, with the highest injury rate among those 85 years and older [2]. Since walking frames are often used by frail and vulnerable older adults; falling, for them, can have very serious consequences on their health.based on these limitations, this work seeks to design a robotic wheeled walker that can be controlled by the user using speech commands and also to reduce the cases of falls experienced by users of the traditional wheeled walking frame. 2. MATERIALS & METHOS The framework of the walker was constructed from wood with the following dimensions: length 25.5cm, width-20.8cm, side-16cm. The EZ-B v3 Bluetooth Robot Controller and the 6AA battery holder were then attached to the side of the framework, while the continuous rotation was attached to the legs of

2 framework using screws. The servos were connected to digital ports ofthe EZ-B v3 Bluetooth Robot Controller via the peripheral cables.connections were also made from the battery to the robot controller, through the adapter, to power the walker. The robotic walker was configured to respond to multiple voice commands using the EZ-Builder Robot Control Software. A block diagram showing how the EZ-B v3 Bluetooth Robot Controller processes speech commands is shown in figure BLOCK IAGRAM The module will trigger an event (navigation) when it detects an audio match of a phrase.the purpose of the robot is to navigate through its environment upon hearing the programmed voice command. This usually takes a maximum of 1.5 seconds. The servos will effect a certain degree of turn to achieve the navigational result. The speed of the robotic walker is 0.1m/s, this can be adjusted using the EZ-Builder robot control software. Phrases are manually configured in the Configuration menu, and custom actions (via script) are assigned to the phrase. The sound frequency accommodated by the speech recognition module is 20Hz to 20 KHz. The programmed speech commands used in this workare Forward (instructs the robot to move forward) Backward (instructs the robot to move backward) Turn Left (instructs the robot to turn left) Right (instructs the robot to turn right) Wait (instructs the robot to stop) ifferent views of the finished robotic wheeled walking frame are shown below in figure 3.7. Fig.3.6 Block diagram showing how the speech commands are processed by the robot controller. The user s speech is converted into an electrical signal by the microphone. The signal is then amplified and converted into adigital signal by the robot controller s analog to digital converter, this is passed on to the speech recognition unit. EEPROM stands for electrically erasable programmable read only memory. It is the internal memory of the controller and holds the programmed speech commands. When the pattern of the user s speech matches a stored pattern, the speech recognition unit passes the information to the microcontroller which sends navigation instructions to the servos through the relay drivers. 4. WORKING PRINCIPLE Bluetooth connection is established between the EZ-B v3 Bluetooth robot controller and the EZ-Builder robot control software through the appropriate port. The user then issues a voice instruction to the walker; this is processed by the EZ-B v3 Bluetooth robot controller.

3 Fig. 3.7 ifferent views of the robotic wheeled walking frame. (a) Front view (b) Back view (c) Side view 5. EZ-BUILER ROBOT CONTROL SOFTWARE The EZ-Builder Robot Control Software is an innovative graphical robot control software for the EZ-B robot controller. The software provides a visual design interface to control your robot creations; it can be used by programmers and non-programmers alike. The image below is what appears on your computer screen upon loading the software. The connection panel is wherebluetooth connection is established between the software and the robot controller through the appropriate port. The Config button on the speech recognition panel is where the speech commands and the custom actions are manually configured. The panels labeled speed are for controlling the servos speed. Fig.3.8 EZ-Builder Robot Control Software version RESULTS The robotic walking frame was tested using the programmed speech commands to observe its response. Five people were selected to issue the commands. They are labeled using letters A, B, C,, E. The commands used for the walker s navigation are Forward, Backward, Turn Left, Right and Wait. The test was carried out in both quiet and noisy environments. Each command was issued twice by the subjects. A control test was also carried out using different sounds. The sounds used are Clapping, Whistling, Finger snapping and Humming. Tables 4.1 and 4.2 shows the results of the speech recognition tests carried out in quiet and noisy environments respectively, while Table 4.3 shows the result of the control test.in the tables, YES means that the walker responded positively to the command, while NO means thewalker s response was negative.

4 Table 4.1 showing the result of speech recognition test carried out in a quiet environment SUBJECTS A B C E COMMANS USE FORWAR BACKWAR TURN LEFT RIGHT WAIT NO YES NO YES YES YES YES YES YES NO YES YES NO YES YES YES NO YES YES YES YES YES YES NO YES YES YES NO YES YES NO YES YES YES NO YES NO YES YES YES YES YES YES NO YES YES NO YES YES YES Table 4.2 showing the result of speech recognition test carried out in a noisy environment SUBJECTS A B C COMMANS USE FORWAR BACKWAR TURN LEFT RIGHT WAIT YES YES NO YES YES NO YES YES YES YES YES YES YES NO YES

5 E YES YES YES YES NO Table 4.3 showing result of the control test carried out with different sound SUBJECTS SOUNS USE CLAPPING WHISTLING FINGER HUMMING SNAPPING A NO NO NO NO B NO NO NO NO C NO NO NO NO NO NO NO NO E NO NO NO NO 7. ISCUSSION Table 4.1 shows the result of the speech recognition test carried out in a quiet environment. There was a 92% positive response by the walker, with 8% of the response being negative. The negative responses recorded were due to; a fall in pitch of the speaker s voice or the speaker not speaking close to the microphone. The results of the test carried out in the noisy environment (television playing loudly) not as favorable with 22% of the response being negative, as shown in table 4.2. This was mostly due to the noise from the television interfering with the speaker s speech. This distorted the speech, and as such, the walker did not respond positively. Table 4.3 shows the result of a testcarried out on the walker using different sounds and not speech commands. This was carried out as a control test in order to eliminate any doubt, whatsoever, as to whether or not the robotic walker responded only to speech. From the results obtained, we ve established that the robotic walker responds to only speech commands that match the onesconfigured in the EZ-Builder software, and that speech recognition is more effective in quiet environments. 8. CONCLUSION AN RECOMMENATION The robotic wheeled walker was constructed and tested successfully using different programmed speech commands. Also, with the incorporation of robotic technology and speech control into the walker, walking will be made easier for the aged especially those with weak hand muscles. This will, hopefully, improve the

6 lives of the aged population and make them more independent. For further improvements on the project, we recommend the following: 1. The robotic walker should be implemented so that the target population can benefit from it. 2. Ultrasonic sensors should be added for obstacle detection, so that people with low vision can also benefit from it. 3. The speech recognition module should be improved upon so that it can be more effective in noisy environments. REFERENCES [1] Rush, K. L., Ouellet, L. L. (1997) Mobility Aids and the Elderly Client. Journal of Gerontological Nursing 23, no. 1: [2] Pedretti, L. (2001). Occupational Therapy: practice skills for physical dysfunction. Mosb, St Louis. [3] Granger C (19. et al 95). An analysis of problems with walkers encountered by elderly persons. 13:1-23. [4] Mulley, G.(1990) Walking Frames. Biomedical Journal 300: [5] Rodriguez L. (2005) Guido, the Robotic SmartWalker for the frail visually impaired. [6] Morris, A. et al (2003) A RoboticWalker That Provides Guidance. Carnegie Mellon University - Pittsburgh, PA. [7] Hutchins, S. (2009) Motorized Walking Frame for Stroke Rehabilitation. University of Salford, UK. [8] Sunder, S. (2002) Textbook of Rehabilitation Jaypee Brothers Medical Publishers (P) Ltd - New ehli. Pp.164. ISBN [9] Nocks, Lisa (2007). The robot: the life story of a technology. Westport, CT: Greenwood Publishing Group. [10] Junqua, J. C. & Haton, J.P. (1995). Robustness in Automatic Speech Recognition: Fundamentals and Applications. Kluwer Academic Publishers. Pp ISBN