1223 53.Rehabilitation and Health Care Robotics H.F.Machiel Van der Loos,David J.Reinkensmeyer The field of rehabilitation robotics develops robotic 53.2 Physical Therapy and Training Robots....1227 systems that assist persons who have a disability 53.2.1 Grand Challenges and Roadblocks..1227 with necessary activities,or that provide therapy 53.2.2 Movement Therapy after Neurologic Injury ..1228 for persons seeking to improve physical or cog- 53.2.3 Robotic Therapy nitive function.This chapter will discuss both of for the Upper Extremity... ..1229 these domains and provide descriptions of the ma- 53.2.4 Robotic Therapy for Walking..........1231 jor achievements of the field over its short history. Specifically,after providing background informa- 53.3 Aids for People with Disabilities. ..1235 tion on world demographics (Sect.53.1.2)and the 53.3.1 Grand Challenges history (Sect.53.1.3)of the field,Sect.53.2 de- and Enabling Technologies.............1235 scribes physical therapy and training robots,and 53.3.2 Types and Examples Sect.53.3 describes robotic aids for people with of Assistive Rehabilitation Robots...1236 disabilities.Section 53.4 then briefly discusses re- cent advances in smart prostheses and orthoses 53.4 Smart Prostheses and Orthoses..............1240 that are related to rehabilitation robotics.Finally, 53.4.1 Grand Challenges and Roadblocks..1240 53.4.2 Targeted Reinnervation.................1240 Sect.53.5 provides an overview of recent work in 53.4.3 Brain-Machine Interfaces diagnosis and monitoring for rehabilitation as well .1241 53.4.4Advances in Neural Stimulation.....1241 as other health-care issues.At the conclusion of 53.4.5 Embedded Intelligence.................1242 this chapter,the reader will be familiar with the history of rehabilitation robotics and its primary 53.5 Augmentation for Diagnosis accomplishments,and will understand the chal- and Monitoring........ ..1242 lenges the field faces in the future as it seeks to 53.5.1 Introduction:Grand Challenges improve health care and the well-being of persons and Enabling Technologies............1242 with disabilities.In this chapter,we will describe 53.5.2 Smart Clinics with Automated an application of robotics that may in the future Health Care Monitoring and Care....1243 touch many of us in an acutely personal way. 53.5.3 Home-Based Rehabilitation Monitoring Systems..1243 53.10 verview....1223 53.5.4Wearable Monitoring Devices.........1244 53.1.1 Taxonomy 53.6 Safety,Ethics,Access,and Economics.....1244 of Rehabilitation Robotics...........1224 53.1.2 World Demographics..................1224 53.7 Conclusions and Further Readings..........1245 53.1.3 Short History of the Field of Rehabilitation Robotics .1225 References..… .1246 53.1 Overview When we become unable to interact physically with when one of our family members,friends or neighbors our immediate environment as we desire in order to is in this situation,we seek technology-based solutions achieve our personal goals through injury or disease,or to assist us in relearning how to complete our activi-
1223 Rehabilitatio 53. Rehabilitation and Health Care Robotics H.F. Machiel Van der Loos, David J. Reinkensmeyer The field of rehabilitation robotics develops robotic systems that assist persons who have a disability with necessary activities, or that provide therapy for persons seeking to improve physical or cognitive function. This chapter will discuss both of these domains and provide descriptions of the major achievements of the field over its short history. Specifically, after providing background information on world demographics (Sect. 53.1.2) and the history (Sect. 53.1.3) of the field, Sect. 53.2 describes physical therapy and training robots, and Sect. 53.3 describes robotic aids for people with disabilities. Section 53.4 then briefly discusses recent advances in smart prostheses and orthoses that are related to rehabilitation robotics. Finally, Sect. 53.5 provides an overview of recent work in diagnosis and monitoring for rehabilitation as well as other health-care issues. At the conclusion of this chapter, the reader will be familiar with the history of rehabilitation robotics and its primary accomplishments, and will understand the challenges the field faces in the future as it seeks to improve health care and the well-being of persons with disabilities. In this chapter, we will describe an application of robotics that may in the future touch many of us in an acutely personal way. 53.1 Overview.............................................. 1223 53.1.1 Taxonomy of Rehabilitation Robotics ............. 1224 53.1.2 World Demographics..................... 1224 53.1.3 Short History of the Field of Rehabilitation Robotics ............. 1225 53.2 Physical Therapy and Training Robots .... 1227 53.2.1 Grand Challenges and Roadblocks .. 1227 53.2.2 Movement Therapy after Neurologic Injury .................. 1228 53.2.3 Robotic Therapy for the Upper Extremity................. 1229 53.2.4 Robotic Therapy for Walking .......... 1231 53.3 Aids for People with Disabilities............. 1235 53.3.1 Grand Challenges and Enabling Technologies ............ 1235 53.3.2 Types and Examples of Assistive Rehabilitation Robots... 1236 53.4 Smart Prostheses and Orthoses .............. 1240 53.4.1 Grand Challenges and Roadblocks .. 1240 53.4.2 Targeted Reinnervation................. 1240 53.4.3 Brain–Machine Interfaces ............. 1241 53.4.4Advances in Neural Stimulation ..... 1241 53.4.5Embedded Intelligence ................. 1242 53.5 Augmentation for Diagnosis and Monitoring .................................... 1242 53.5.1 Introduction: Grand Challenges and Enabling Technologies ............ 1242 53.5.2 Smart Clinics with Automated Health Care Monitoring and Care.... 1243 53.5.3 Home-Based Rehabilitation Monitoring Systems ...................... 1243 53.5.4Wearable Monitoring Devices......... 1244 53.6 Safety, Ethics, Access, and Economics ..... 1244 53.7 Conclusions and Further Readings.......... 1245 References .................................................. 1246 53.1 Overview When we become unable to interact physically with our immediate environment as we desire in order to achieve our personal goals through injury or disease, or when one of our family members, friends or neighbors is in this situation, we seek technology-based solutions to assist us in relearning how to complete our activiPart F 53
1224 Part F Field and Service Robotics ties of daily living(ADLs).or to assist us in actually Assistive robots are generally grouped accord- doing them if we are unable to relearn.While hu- ing to whether they focus on manipulation,mobility, man therapists and attendants can indeed provide the or cognition.Manipulation aids are further classi- types of assistance required,the projected short-term fied into fixed-platform,portable-platform,and mobile demographics of China,Japan,and the Scandinavian autonomous types.Fixed-platform robots perform func- countries show a growing shortage of working-age tions in the kitchen,on the desktop,or by the bed. adults.Age-related disabilities will soon dominate the Portable types are manipulator arms attached to an elec- service sector job market,put many older and disabled tric wheelchair to hold and move objects and to interact people at risk,and increase the need for institutional- with other devices and equipment,as in opening a door. ization when there is no viable home-based solution.Mobile autonomous robots can be controlled by voice or National programs to develop personal robots,robotic other means to carry out manipulation and other errands therapy,smart prostheses,smart beds,smart homes,in the home or workplace.Mobility aids are divided and tele-rehabilitation services have accelerated in the into electric wheelchairs with navigation systems and past ten years and will need to continue apace with the mobile robots that act as smart,motorized walkers,al- ever-increasing ability of health care to allow people to lowing people with mobility impairments to lean on live longer through the repression of disease and im-them to prevent falls and provide stability.The third main provements in surgical and medication interventions. type,cognitive aids,assist people who have dementia, Rehabilitation robotics,although only a 40-year-old dis- autism or other disorders that affect communication and cipline [53.1-3],is projected to grow quickly in the physical well-being. coming decades. The fields of prosthetics and FNS are closely al- 驾 lied with rehabilitation robotics.Prostheses are artificial 53.1.1 Taxonomy of Rehabilitation Robotics hands,arms,legs,and feet that are worn by the user to replace amputated limbs.Prostheses are increasingly The field of rehabilitation robotics is generally divided incorporating robotic features.FNS systems seek to into the categories of therapy and assistance robots.In reanimate the limb movements of weak or paralyzed addition,rehabilitation robotics includes aspects of arti- people by electrically stimulating nerve and muscle. ficial limb(prosthetics)development,functional neural FNS control systems are analogous to robotic control stimulation,(FNS)and technology for the diagnosis and systems,except that the actuators being controlled are monitoring of people during ADLs. human muscles.Another related field is technology for Therapy robots generally have at least two main monitoring and diagnosing health care issues as a person users simultaneously,the person with a disability who performs ADLs. is receiving the therapy and the therapist who sets up The chapter is organized according to this taxonomy. and monitors the interaction with the robot.Types of After providing background information on world de- therapy that have benefited from robotic assistance are mographics (Sect.53.1.2)and the history (Sect.53.1.3) upper-and lower-extremity movement therapy,enabling of the field,Sect.53.2 describes physical therapy and communication for children with autism,and enabling training robots,and Sect.53.3 describes robotic aids exploration (education)for children with cerebral palsy for people with disabilities.Section 53.4 then reviews (CP)or other developmental disabilities.A robot may be recent advances in smart prostheses and orthoses that a good alternative to a physical or occupational therapist are related to rehabilitation robotics.Finally,Sect.53.5 for the actual hands-on intervention for several reasons: provides an overview of recent work in diagnosis and (1)once properly set up,an automated exercise machine monitoring for rehabilitation as well as other health care can consistently apply therapy over long periods of time issues. without tiring;(2)the robot's sensors can measure the work performed by the patient and quantify,to an extent 53.1.2 World Demographics perhaps not yet measurable by clinical scales,any re- covery of function that may have occurred,which may The various areas of rehabilitation robotics focus on be highly motivating for a person to continue with the different user populations,but a common characteris- therapy;and(3)the robot may be able to engage the tic of these populations is that they have a disability. patient in types of therapy exercises that a therapist can- Disability is defined in the Americans with Disabilities not do,such as magnifying movement errors to provoke Act as "a physical or mental impairment that substan- adaptation [53.4,5]. tially limits one or more of the major life activities
1224 Part F Field and Service Robotics ties of daily living (ADLs), or to assist us in actually doing them if we are unable to relearn. While human therapists and attendants can indeed provide the types of assistance required, the projected short-term demographics of China, Japan, and the Scandinavian countries show a growing shortage of working-age adults. Age-related disabilities will soon dominate the service sector job market, put many older and disabled people at risk, and increase the need for institutionalization when there is no viable home-based solution. National programs to develop personal robots, robotic therapy, smart prostheses, smart beds, smart homes, and tele-rehabilitation services have accelerated in the past ten years and will need to continue apace with the ever-increasing ability of health care to allow people to live longer through the repression of disease and improvements in surgical and medication interventions. Rehabilitation robotics, although only a 40-year-old discipline [53.1–3], is projected to grow quickly in the coming decades. 53.1.1 Taxonomy of Rehabilitation Robotics The field of rehabilitation robotics is generally divided into the categories of therapy and assistance robots. In addition, rehabilitation robotics includes aspects of arti- ficial limb (prosthetics) development, functional neural stimulation, (FNS) and technology for the diagnosis and monitoring of people during ADLs. Therapy robots generally have at least two main users simultaneously, the person with a disability who is receiving the therapy and the therapist who sets up and monitors the interaction with the robot. Types of therapy that have benefited from robotic assistance are upper- and lower-extremity movement therapy, enabling communication for children with autism, and enabling exploration (education) for children with cerebral palsy (CP) or other developmental disabilities. A robot may be a good alternative to a physical or occupational therapist for the actual hands-on intervention for several reasons: (1) once properly set up, an automated exercise machine can consistently apply therapy over long periods of time without tiring; (2) the robot’s sensors can measure the work performed by the patient and quantify, to an extent perhaps not yet measurable by clinical scales, any recovery of function that may have occurred, which may be highly motivating for a person to continue with the therapy; and (3) the robot may be able to engage the patient in types of therapy exercises that a therapist cannot do, such as magnifying movement errors to provoke adaptation [53.4, 5]. Assistive robots are generally grouped according to whether they focus on manipulation, mobility, or cognition. Manipulation aids are further classi- fied into fixed-platform, portable-platform, and mobile autonomous types. Fixed-platform robots perform functions in the kitchen, on the desktop, or by the bed. Portable types are manipulator arms attached to an electric wheelchair to hold and move objects and to interact with other devices and equipment, as in opening a door. Mobile autonomous robots can be controlled by voice or other means to carry out manipulation and other errands in the home or workplace. Mobility aids are divided into electric wheelchairs with navigation systems and mobile robots that act as smart, motorized walkers, allowing people with mobility impairments to lean on them to prevent falls and provide stability. The third main type, cognitive aids, assist people who have dementia, autism or other disorders that affect communication and physical well-being. The fields of prosthetics and FNS are closely allied with rehabilitation robotics. Prostheses are artificial hands, arms, legs, and feet that are worn by the user to replace amputated limbs. Prostheses are increasingly incorporating robotic features. FNS systems seek to reanimate the limb movements of weak or paralyzed people by electrically stimulating nerve and muscle. FNS control systems are analogous to robotic control systems, except that the actuators being controlled are human muscles. Another related field is technology for monitoring and diagnosing health care issues as a person performs ADLs. The chapter is organized according to this taxonomy. After providing background information on world demographics (Sect. 53.1.2) and the history (Sect. 53.1.3) of the field, Sect. 53.2 describes physical therapy and training robots, and Sect. 53.3 describes robotic aids for people with disabilities. Section 53.4 then reviews recent advances in smart prostheses and orthoses that are related to rehabilitation robotics. Finally, Sect. 53.5 provides an overview of recent work in diagnosis and monitoring for rehabilitation as well as other health care issues. 53.1.2 World Demographics The various areas of rehabilitation robotics focus on different user populations, but a common characteristic of these populations is that they have a disability. Disability is defined in the Americans with Disabilities Act as “a physical or mental impairment that substantially limits one or more of the major life activities.” Part F 53.1
Rehabilitation and Health Care Robotics 53.1 Overview 1225 Table 53.1 Prevalence and incidence of disability and aging in selected countries [53.6] Country Number of people Percentage of population Number of elderly Percentage of population with disabilities with disabilities people that is elderly France 5146000 83 12151000 19.6 USA 52591000 20.0 35000000 12.4 Great Britain 4453000 7.3 12200000 29.5 The Netherlands 1432000 9.5 2118808 13.4 Spain 3528220 8.9 6936000 17.6 Japan 5136000 4.3 44982000 35.7 Korea 3195000 7.1 16300000 36.0 In the industrialized countries (e.g.,Japan,US,Canada, (early 1970s)(reviewed in [53.7])were both adaptations and Europe),the incidence of disability varies between of replacement mechanical arms meant as powered or- 8%and 20%,with differences likely due primarily to thoses [53.1].The user drove the Golden Arm with a set varying definitions of disability and reporting conven- of tongue-operated switches,joint-by-joint,an arduous tions (Table 53.1).Age is a risk factor for disability,and means of endpoint control.In the mid 1970s,the De- lower birth rates and life-extending health care are the partment of Veterans Affairs began funding a group at dominant factors contributing to the aging of the pop- the Applied Physics Lab under the guidance of Seamone ulation and a concomitant rise in disability.In China,and Schmeisser to computerize an orthosis mounted on the population control policies of the 1970s have created a workstation to do activities of daily living(ADL)tasks art alack of working-age adults to support theeconomy.The such as feeding a person and turning pages [53.9].For disproportionate incidence of disability in the elderly the first time,a rehabilitation robot had a command-type population makes it clear that developers of rehabili-interface,not just a joint-by-joint motion controller. tation robotics will also be faced with users who,as The 1970s also saw the French Spartacus system be- a demographic group,generally have lower levels of ing developed,guided by the vision of Jean Vertut,for sensory and motor capability,and may have impaired use by people with high-level spinal cord injury as well cognition as well.The urgency of making advances in as children with cerebral palsy [53.10].This system did this field is increasing in line with these demographic not emerge from the P&O field but was developed by changes. the French Atomic Energy Commission(CEA),which used large telemanipulators for nuclear fuel rod han- 53.1.3 Short History of the Field dling.One of these was adapted so that people with of Rehabilitation Robotics movement impairment could control it using a joystick for pick-and-place tasks.A decade later,one of the re- The history of rehabilitation robotics is almost as old as searchers on the Spartacus project,Hok Kwee,began the that of robotics itself,although emanating from very dif-MANUS project,a dedicated effort to develop the first ferent sources.Several books,chapters,and papers have wheelchair-mounted manipulator designed expressly as been written on the history of rehabilitation robotics in a rehabilitation robot,not adapted from a design from more detail than this section [53.1,7,8],and numerous another field. papers in the proceedings of the Institute of Electrical However,in between,several other major programs and Electronics Engineers (IEEE)International Con- were begun.In 1978,at Stanford University,and then ference on Rehabilitation Robotics also provide more with decades-long funding from the US Department of grounding for historical perspective.The chronology Veterans Affairs,Larry Leifer started the vocational as- below pays particular attention to early work and to sistant robot program,culminating in several clinically projects with notable clinical and/or commercial impact.tested versions of the desktop vocational assistant robot Early robotics,starting in the late 1950s,focused (DeVAR)[53.3,11,12],a mobile version,the mobile vo- on large manipulators to replace workers in factories cational assistant robot(MoVAR)[53.13],and finally the for dirty,dangerous,and undesirable tasks.The earliest professional vocational assistant robot(ProVAR),which rehabilitation robots came from the field of prosthet-had the advanced ability for the user to program tasks in ics and orthotics(P&O).The Case Western University an easy-to-use browser-type environment [53.14].This arm (1960s)and the Rancho Los Amigos Golden Arm step was made since,although DeVAR made it briefly
Rehabilitation and Health Care Robotics 53.1 Overview 1225 Table 53.1 Prevalence and incidence of disability and aging in selected countries [53.6] Country Number of people Percentage of population Number of elderly Percentage of population with disabilities with disabilities people that is elderly France 5 146 000 8.3 12 151 000 19.6 USA 52 591 000 20.0 35 000 000 12.4 Great Britain 4 453 000 7.3 12 200 000 29.5 The Netherlands 1 432 000 9.5 2 118 808 13.4 Spain 3 528 220 8.9 6 936 000 17.6 Japan 5 136 000 4.3 44 982 000 35.7 Korea 3 195 000 7.1 16 300 000 36.0 In the industrialized countries (e.g., Japan, US, Canada, and Europe), the incidence of disability varies between 8% and 20%, with differences likely due primarily to varying definitions of disability and reporting conventions (Table 53.1). Age is a risk factor for disability, and lower birth rates and life-extending health care are the dominant factors contributing to the aging of the population and a concomitant rise in disability. In China, the population control policies of the 1970s have created a lack of working-age adults to support the economy. The disproportionate incidence of disability in the elderly population makes it clear that developers of rehabilitation robotics will also be faced with users who, as a demographic group, generally have lower levels of sensory and motor capability, and may have impaired cognition as well. The urgency of making advances in this field is increasing in line with these demographic changes. 53.1.3 Short History of the Field of Rehabilitation Robotics The history of rehabilitation robotics is almost as old as that of robotics itself, although emanating from very different sources. Several books, chapters, and papers have been written on the history of rehabilitation robotics in more detail than this section [53.1, 7, 8], and numerous papers in the proceedings of the Institute of Electrical and Electronics Engineers (IEEE) International Conference on Rehabilitation Robotics also provide more grounding for historical perspective. The chronology below pays particular attention to early work and to projects with notable clinical and/or commercial impact. Early robotics, starting in the late 1950s, focused on large manipulators to replace workers in factories for dirty, dangerous, and undesirable tasks. The earliest rehabilitation robots came from the field of prosthetics and orthotics (P&O). The Case Western University arm (1960s) and the Rancho Los Amigos Golden Arm (early 1970s) (reviewed in [53.7]) were both adaptations of replacement mechanical arms meant as powered orthoses [53.1]. The user drove the Golden Arm with a set of tongue-operated switches, joint-by-joint, an arduous means of endpoint control. In the mid 1970s, the Department of Veterans Affairs began funding a group at the Applied Physics Lab under the guidance of Seamone and Schmeisser to computerize an orthosis mounted on a workstation to do activities of daily living (ADL) tasks such as feeding a person and turning pages [53.9]. For the first time, a rehabilitation robot had a command-type interface, not just a joint-by-joint motion controller. The 1970s also saw the French Spartacus system being developed, guided by the vision of Jean Vertut, for use by people with high-level spinal cord injury as well as children with cerebral palsy [53.10]. This system did not emerge from the P&O field but was developed by the French Atomic Energy Commission (CEA), which used large telemanipulators for nuclear fuel rod handling. One of these was adapted so that people with movement impairment could control it using a joystick for pick-and-place tasks. A decade later, one of the researchers on the Spartacus project, Hok Kwee, began the MANUS project, a dedicated effort to develop the first wheelchair-mounted manipulator designed expressly as a rehabilitation robot, not adapted from a design from another field. However, in between, several other major programs were begun. In 1978, at Stanford University, and then with decades-long funding from the US Department of Veterans Affairs, Larry Leifer started the vocational assistant robot program, culminating in several clinically tested versions of the desktop vocational assistant robot (DeVAR) [53.3,11,12], a mobile version, the mobile vocational assistant robot (MoVAR) [53.13], and finally the professional vocational assistant robot (ProVAR), which had the advanced ability for the user to program tasks in an easy-to-use browser-type environment [53.14]. This step was made since, although DeVAR made it briefly Part F 53.1
1226 Part F Field and Service Robotics onto the market in the early 1990s,multisite user test- Rich Mahoney,moved to ARC and was instrumental ing revealed it was still too costly for the functionality in extending the company's repertoire to the RAPTOR it had:ProVAR development ensued,then continued by wheelchair-mounted arm [53.18]. Machiel Van der Loos.All these versions were based In Europe,the most significant mobile manipula- on the Puma-260 industrial manipulator to achieve ro- tor project was the MANUS project [53.19]mentioned bust,safe operation.Research shifted in 2006 to the earlier.With much of the work done under the di- Veterans Affairs(VA)in Syracuse,NY,to integrate sens- rection of Hok Kwee at the Rehabilitation Research ing and autonomous features and explore new,more and Development Center (iRV)in the Netherlands,the cost-effective manipulator options. project culminated in a robot specifically designed for In the mid 1980s.from observations on the wheelchair mounting,with control through a joystick unsuitability of existing industrial,educational,and and feedback by a small display on the arm itself.This orthosis-derived manipulators for rehabilitation appli- project has led to numerous follow-on research projects, cations,Tim Jones at Universal Machine Intelligence and,most significantly,to the commercialization of the (later Oxford Intelligent Machines,OxIM)in the UK system by Exact Dynamics BV,in the Netherlands.It is began an intensive effort to provide the rehabilitation currently offered free on physician prescription by the robotics community with its first workhorse system spe- Dutch government to qualified people with a disability cially designed from the ground up for human service such as cerebral palsy or tetraplegia from a spinal cord tasks.Over ten years,a series of systems,starting with injury. the RTX model,were used in numerous research labs and Autonomous navigation systems on electric clinics around the world.The most extensive effort to wheelchairs also began in the 1980s,benefiting initially use the OxIM arm was in France,and a suite of research from the development by Polaroid Corporation of range projects,funded by the French government and the Eu- finders for its cameras using ultrasonic sensors.They ropean Research Commission,starting as the robot for were inexpensive,and small enough,at 30 mm in diam- assisting the integration of the disabled(RAID),then eter,that dozens of them could be placed around the as MASTER [53.15],developed and clinically tested periphery of a wheelchair to aid medium-range navi- workstation-based assistive systems based on the RTX gation 10-500cm).In the 1990s and early 2000s, and subsequent OxIM arms.When OxIM ceased build- with the advent of vision-based servoing and laser range ing its arms,the French company Afma Robotics [53.16] scanners,algorithms for faster,smarter,less-error-prone took over efforts to commercialize the MASTER system, navigation and obstacle avoidance dominated research which it continues to do today (2007). advances in this sector.In Korea,for example,Zenn Bien The UK was also the site of the first commercially at the Korea Advanced Institute for Science and Tech- available feeding robot,Handy-I,an inexpensive and nology(KAIST)Human Welfare Robotics Center began well-received device first designed by Mike Topping developing the KAIST rehabilitation engineering system and then commercialized by Rehabilitation Robotics. (KARES)line of wheelchair-based navigation systems Ltd.in the 1990s [53.17].Primarily aimed to enabled in the late 1990s [53.20]and the NavChair project at the people with cerebral palsy to achieve a measure of in- University of Michigan was the start of a development dependence in feeding themselves,task environments line that led to the commercialized Hephaestus system later also included face washing and the application of at the University of Pittsburgh [53.21,22]. cosmetics,areas of high demand identified by its users. Therapy robots had a later start than assistive robots, The history of mobile manipulator applications be- with early exercise devices such as the BioDex [53.23] gan in the 1980s with adaptations of educational and a first step in programmable,force-controlled,albeit industrial robots,and achieved a boost with the funding single-axis devices,in the mid 1980s.The first multi-axis of the US National Institute on Disability and Rehabilita- concept was published by Khalili and Zomlefer [53.24], tion Research(NIDRR)for a Rehabilitation Engineering and the first tested system by Robert Erlandson at Research Center on Rehabilitation Robotics (RERC)Wayne State University emerged in the mid 1980s at the Alfred I.duPont Hospital in Delaware from as well [53.25].The RTX manipulator had a touch- 1993-1997.With its ability to fund dozens of research sensitive pad as an end-effector,presenting targets at projects in parallel,it also formed a partnership with different locations for patients with upper-extremity a local company,Applied Resources,Corp.(ARC), weakness (e.g.,following a stroke)to hit after the which developed and marketed several rehabilitation screen gave a visual signal.Software logged response technology products.One of the RERC researchers, times,thereby providing a score that was tallied and
1226 Part F Field and Service Robotics onto the market in the early 1990s, multisite user testing revealed it was still too costly for the functionality it had: ProVAR development ensued, then continued by Machiel Van der Loos. All these versions were based on the Puma-260 industrial manipulator to achieve robust, safe operation. Research shifted in 2006 to the Veterans Affairs (VA) in Syracuse, NY, to integrate sensing and autonomous features and explore new, more cost-effective manipulator options. In the mid 1980s, from observations on the unsuitability of existing industrial, educational, and orthosis-derived manipulators for rehabilitation applications, Tim Jones at Universal Machine Intelligence (later Oxford Intelligent Machines, OxIM) in the UK began an intensive effort to provide the rehabilitation robotics community with its first workhorse system specially designed from the ground up for human service tasks. Over ten years, a series of systems, starting with the RTX model, were used in numerous research labs and clinics around the world. The most extensive effort to use the OxIM arm was in France, and a suite of research projects, funded by the French government and the European Research Commission, starting as the robot for assisting the integration of the disabled (RAID), then as MASTER [53.15], developed and clinically tested workstation-based assistive systems based on the RTX and subsequent OxIM arms. When OxIM ceased building its arms, the French company Afma Robotics [53.16] took over efforts to commercialize the MASTER system, which it continues to do today (2007). The UK was also the site of the first commercially available feeding robot, Handy-I, an inexpensive and well-received device first designed by Mike Topping and then commercialized by Rehabilitation Robotics, Ltd. in the 1990s [53.17]. Primarily aimed to enabled people with cerebral palsy to achieve a measure of independence in feeding themselves, task environments later also included face washing and the application of cosmetics, areas of high demand identified by its users. The history of mobile manipulator applications began in the 1980s with adaptations of educational and industrial robots, and achieved a boost with the funding of the US National Institute on Disability and Rehabilitation Research (NIDRR) for a Rehabilitation Engineering Research Center on Rehabilitation Robotics (RERC) at the Alfred I. duPont Hospital in Delaware from 1993–1997. With its ability to fund dozens of research projects in parallel, it also formed a partnership with a local company, Applied Resources, Corp. (ARC), which developed and marketed several rehabilitation technology products. One of the RERC researchers, Rich Mahoney, moved to ARC and was instrumental in extending the company’s repertoire to the RAPTOR wheelchair-mounted arm [53.18]. In Europe, the most significant mobile manipulator project was the MANUS project [53.19] mentioned earlier. With much of the work done under the direction of Hok Kwee at the Rehabilitation Research and Development Center (iRV) in the Netherlands, the project culminated in a robot specifically designed for wheelchair mounting, with control through a joystick and feedback by a small display on the arm itself. This project has led to numerous follow-on research projects, and, most significantly, to the commercialization of the system by Exact Dynamics BV, in the Netherlands. It is currently offered free on physician prescription by the Dutch government to qualified people with a disability such as cerebral palsy or tetraplegia from a spinal cord injury. Autonomous navigation systems on electric wheelchairs also began in the 1980s, benefiting initially from the development by Polaroid Corporation of range finders for its cameras using ultrasonic sensors. They were inexpensive, and small enough, at 30 mm in diameter, that dozens of them could be placed around the periphery of a wheelchair to aid medium-range navigation (≈ 10–500 cm). In the 1990s and early 2000s, with the advent of vision-based servoing and laser range scanners, algorithms for faster, smarter, less-error-prone navigation and obstacle avoidance dominated research advances in this sector. In Korea, for example, Zenn Bien at the Korea Advanced Institute for Science and Technology (KAIST) Human Welfare Robotics Center began developing the KAIST rehabilitation engineering system (KARES) line of wheelchair-based navigation systems in the late 1990s [53.20] and the NavChair project at the University of Michigan was the start of a development line that led to the commercialized Hephaestus system at the University of Pittsburgh [53.21, 22]. Therapy robots had a later start than assistive robots, with early exercise devices such as the BioDex [53.23] a first step in programmable, force-controlled, albeit single-axis devices, in the mid 1980s. The first multi-axis concept was published by Khalili and Zomlefer [53.24], and the first tested system by Robert Erlandson at Wayne State University emerged in the mid 1980s as well [53.25]. The RTX manipulator had a touchsensitive pad as an end-effector, presenting targets at different locations for patients with upper-extremity weakness (e.g., following a stroke) to hit after the screen gave a visual signal. Software logged response times, thereby providing a score that was tallied and Part F 53.1
Rehabilitation and Health Care Robotics 53.2 Physical Therapy and Training Robots 1227 compared to previous sessions.Later robots used ad- several demonstration systems were developed.In the vanced force-based control,which required significantly early 2000s,Corinna Latham of Anthrotronix,Inc.com- more computer power.The early 1990s saw the start mercialized small robot systems to enable children with of the MIT-MANUS Project with Neville Hogan and physical disabilities to play games with simple inter- Igo Krebs,followed a few years later by the Palo Alto faces.Later.small mobile robots were used in clinics VA mirror image movement enabler(MIME)project by Kerstin Dautenhahn's group [53.26]with children and its derivative,Driver's simulation environment for who have autism;since robots have such simple inter- arm therapy (SEAT),with Charles Burgar,Machiel Van faces,communication with them does not appear not der Loos,and Peter Lum,as well as the Rehabilita-be as challenging as with other humans.The early tion Institute of Chicago ARM project with Zev Rymer 2000s also saw the advent of pet robots,such as the and David Reinkensmeyer.Each had a different phi- Paro seal robot developed by Shibata et al.[53.27],as losophy on upper-extremity stroke therapy and each companions for both children and the elderly who are was able to demonstrate clinical effectiveness in a dif- confined to clinics and have limited real companion- ferent way.All three programs,now a decade later,ship. have made significant technical advances and are still The applications for robotics continue to increase active. in number as advances in materials.control software, Cognitive robotics had a start in the early 1980s to higher robustness and the diminishing size of sensors aid children with communication disorders and physi-and actuators allow designers to attempt new ways of cal disorders to achieve a measure of control of their using mechatronics technology to further the well-being physical space.Using mostly educational manipulators, of people with disabilities. 53.2 Physical Therapy and Training Robots 53.2.1 Grand Challenges and Roadblocks nize beginning in the late 1980s,neuro-rehabilitation is a logical target for automation because of its labor- The human neuromuscular system exhibits use-intensive,mechanical nature,and because the amount of dependent plasticity,which is to say that use alters the recovery is linked with the amount of repetition.Robots properties of neurons and muscles,including the pattern could deliver at least the repetitive parts of movement of their connectivity,and thus their function [53.28-30]. therapy at lower cost than human therapists,allowing The process of neuro-rehabilitation seeks to exploit this patients to receive more therapy. use-dependent plasticity in order to help people re- The grand challenge for automating movement ther- learn how to move following neuromuscular injuries or apy is determining how to optimize use-dependent diseases.Neuro-rehabilitation is typically provided by plasticity.That is,researchers in this field must de- skilled therapists,including physical,occupational and termine what the robot should do in cooperation with speech therapists.This process is time-consuming,in-the patient's own movement attempts in order to maxi- volving daily,intensive movement practice over many mally improve movement ability.Meeting this challenge weeks.It is also labor-intensive,requiring hands-on involves solving two key problems:determining appro- assistance from therapists.For some tasks,such as teach- priate movement tasks(what movements should patients ing a person with poor balance and weak legs to walk, practise and what feedback should they receive about this hands-on assistance requires that the therapist have their performance),and determining an appropriate pat- substantial strength and agility. tern of mechanical input to the patient during these Because neuro-rehabilitation is time-and labor-movement tasks(what forces should the robot apply to intensive,in recent years health care payers have put the patient's limb to provoke plasticity).The prescription limits on the amount of therapy that they will pay for,in of movement tasks and mechanical input fundamen- an effort to contain spiraling health care costs.Ironically,tally constrains the mechanical and control design of at the same time,there has been increasing scientific ev- the robotic therapy device. idence that more therapy can in some cases increase There are two main roadblocks to achieving the movement recovery via use-dependent plasticity.As grand challenge.The first is a scientific roadblock: robotics and rehabilitation researchers began to recog- neither the optimal movement tasks nor the optimal
Rehabilitation and Health Care Robotics 53.2 Physical Therapy and Training Robots 1227 compared to previous sessions. Later robots used advanced force-based control, which required significantly more computer power. The early 1990s saw the start of the MIT-MANUS Project with Neville Hogan and Igo Krebs, followed a few years later by the Palo Alto VA mirror image movement enabler (MIME) project and its derivative, Driver’s simulation environment for arm therapy (SEAT), with Charles Burgar, Machiel Van der Loos, and Peter Lum, as well as the Rehabilitation Institute of Chicago ARM project with Zev Rymer and David Reinkensmeyer. Each had a different philosophy on upper-extremity stroke therapy and each was able to demonstrate clinical effectiveness in a different way. All three programs, now a decade later, have made significant technical advances and are still active. Cognitive robotics had a start in the early 1980s to aid children with communication disorders and physical disorders to achieve a measure of control of their physical space. Using mostly educational manipulators, several demonstration systems were developed. In the early 2000s, Corinna Latham of Anthrotronix, Inc. commercialized small robot systems to enable children with physical disabilities to play games with simple interfaces. Later, small mobile robots were used in clinics by Kerstin Dautenhahn’s group [53.26] with children who have autism; since robots have such simple interfaces, communication with them does not appear not be as challenging as with other humans. The early 2000s also saw the advent of pet robots, such as the Paro seal robot developed by Shibata et al. [53.27], as companions for both children and the elderly who are confined to clinics and have limited real companionship. The applications for robotics continue to increase in number as advances in materials, control software, higher robustness and the diminishing size of sensors and actuators allow designers to attempt new ways of using mechatronics technology to further the well-being of people with disabilities. 53.2 Physical Therapy and Training Robots 53.2.1 Grand Challenges and Roadblocks The human neuromuscular system exhibits usedependent plasticity, which is to say that use alters the properties of neurons and muscles, including the pattern of their connectivity, and thus their function [53.28–30]. The process of neuro-rehabilitation seeks to exploit this use-dependent plasticity in order to help people relearn how to move following neuromuscular injuries or diseases. Neuro-rehabilitation is typically provided by skilled therapists, including physical, occupational and speech therapists. This process is time-consuming, involving daily, intensive movement practice over many weeks. It is also labor-intensive, requiring hands-on assistance from therapists. For some tasks, such as teaching a person with poor balance and weak legs to walk, this hands-on assistance requires that the therapist have substantial strength and agility. Because neuro-rehabilitation is time- and laborintensive, in recent years health care payers have put limits on the amount of therapy that they will pay for, in an effort to contain spiraling health care costs. Ironically, at the same time, there has been increasing scientific evidence that more therapy can in some cases increase movement recovery via use-dependent plasticity. As robotics and rehabilitation researchers began to recognize beginning in the late 1980s, neuro-rehabilitation is a logical target for automation because of its laborintensive, mechanical nature, and because the amount of recovery is linked with the amount of repetition. Robots could deliver at least the repetitive parts of movement therapy at lower cost than human therapists, allowing patients to receive more therapy. The grand challenge for automating movement therapy is determining how to optimize use-dependent plasticity. That is, researchers in this field must determine what the robot should do in cooperation with the patient’s own movement attempts in order to maximally improve movement ability. Meeting this challenge involves solving two key problems: determining appropriate movement tasks (what movements should patients practise and what feedback should they receive about their performance), and determining an appropriate pattern of mechanical input to the patient during these movement tasks (what forces should the robot apply to the patient’s limb to provoke plasticity). The prescription of movement tasks and mechanical input fundamentally constrains the mechanical and control design of the robotic therapy device. There are two main roadblocks to achieving the grand challenge. The first is a scientific roadblock: neither the optimal movement tasks nor the optimal Part F 53.2