[ARTICLE] Feasibility Analysis Of Daily Activities Using Assistive Robotic Manipulators – Full Text

ABSTRACT

In the United States, more than 21.5 million people report a limitation in their self-care activities and independent living. Assistive robotic manipulators (ARMs) can provide assistance with daily tasks for people with upper extremity impairments. Previous studies have evaluated ARM efficacy in completing single and multiple action tasks. This paper presents the feasibility analysis of two sequential daily self-care activities, brushing teeth and preparing and then eating a simple meal. The two tasks were successfully completed by a well-trained investigator using the ARM. By analyzing the difficulties and failures in the testing, the ARM’s kinematic and dynamic limitations and the kinesthetic perceptions made it difficult to re-adjust motion planning before errors occurred. In addition, we provide an example to alleviate environmental limitations. Due to the differences between the ARM and human motions, some intuitive human motion plans were not applicable to the ARM motion. The results of this work may help researchers and clinicians develop appropriate accessories, make adequate environmental adjustments, and tailor training for ARM users.

BACKGROUND

In the United States, more than 21.5 million people report limitations in the self-care activities and independent living (Erickson, Lee, & von Schrader, 2014), such as dressing and eating and doing errands alone. In addition, a growing older adult population with moderate to severe disabilities is estimated to reach 24.6 million people in 2040 (Johnson, 2007). Assistive robot manipulators (ARMs) have emerged as a tool to assist with activities of daily living (ADLs) (Allin, Eckel, Markham, & Brewer, 2010). Commercial ARMs such as iARM by the Exact Dynamics (Dindom, The Netherlands) and JACO by Kinova (Montreal, Canada), were developed to assist people with upper extremity impairments with manipulation tasks in their daily living and increase their independence (Driessen, Evers, & Van Woerden, 2001; Maheu, Archambault, Frappier, & Routhier, 2011).

The adaptation of new assistive technologies requires not only a solid understanding of the interface but also new ways in performing tasks. For example, a new power wheelchair user has to learn not only the joystick control interface but also develop new strategies to move around places due to the limitation of the mobility device. Similarly, better ARM performance relies on both the efficient control interface and fluid motion planning. Studies evaluated the ARM control efficiency using various levels of ADL tasks: single action, multiple actions, and sequential tasks (Chung, Wang, & Cooper, 2013), shown in Table 1. These studies evaluated ARM performance using single or multiple action tasks, such as pick-and-place and pushing buttons and evaluated users’ abilities with different control interfaces. However, most ADL tasks are sequential, which are the combinations of successful completion of single and multiple actions in a suitable sequence. A complete eating sequence includes not only scooping of food and placing a spoon in the mouth but also applying different motion plans to collect food from different locations in the bowl.

Several studies (Chung, Hannan, Wang, Kelleher, & Cooper, 2014; Chung, Wang, Kelleher, & Cooper, 2013) were conducted to evaluate the ARM efficacy with standardized performance evaluation tools that can minimize environmental variability so that performance from different studies can be easily contrasted or compared. These studies revealed statistical differences in the efficacy of ARM performance across tasks. Noticeably, better performance on the standardized tools may lead to less errors and faster performance in the sequential tasks. However, most ARM studies were evaluated in lab settings. The feasibility using common objects within ordinary environments remains to be determined. Additionally, few studies have reported the limitations and challenges of ARM performance under real life situations.

Thus, in this study, we assessed the feasibility of two sequential self-care tasks, brushing teeth and preparing and then eating a simple meal. Successful motion planning in conjunction with the limitations and challenges under real life situations were examined to help researchers and clinicians develop appropriate accessories and make adequate environmental adjustments for ARM users.

Figure 1. Two sequential tasks (Left: brushing teeth, Right: preparing and then having a simple meal)

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