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Technology for Adaptive Aging 3 Movement Control in the Older Adult Caroline J. Ketcham and George E. Stelmach INTRODUCTION The control of movements is a complex interaction of cognitive and sensorimotor systems. Researchers in movement science aim to understand how an action is produced and what mechanisms are involved in regulating the movement. Motor control declines in older adults include changes in both the peripheral and the central nervous system, which lead to an array of behavioral decrements (Salthouse, 1985; Welford, 1977; Ketcham and Stelmach, 2002). It is well known that as adults age, the execution of movement becomes slow and more variable, and there is emerging evidence that the microstructure of the movement also changes. In this chapter we document most of the major changes that occur in the control and coordination of movement with respect to aging. In the studies reviewed, older adults are classified as over 60 years and are compared with young adults typically between 18 and 30 years of age in a cross-sectional manner (see Schaie, this volume, for a methodological description). Results reported are means derived from age-group comparisons and do not address individual differences. The review begins with a discussion of processing speed defined by reaction time and presents differences between young and older adults on simple and complex tasks. The following topics include changes that occur in older adults related to the control of movement including: reduced movement speed, movement composition differences, increased variability, reduced force control, and coordination difficulties. Subsequently highlighted are some of the possible sensorimotor changes that
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Technology for Adaptive Aging may contribute to slower, more-variable movements and reduced strength observed in older adults. Changes in posture and balance are then discussed, as a stable base of support is necessary to execute precise motor skills as well as being important for mobility of older adults. Finally, an overview of motor learning research as well as a discussion of improvements in motor function with generalized and specific training programs are presented. As is apparent, changes in control and coordination of movement significantly affect the type of activities that older adults can efficiently perform and often determine whether they can live independently. Thus, those involved in enhancing the performance capabilities of these individuals need to have a good understanding of how the aging processes diminish motor performance. RESPONSE INITIATION Reaction time is defined as the time required to initiate a movement response following a visual, auditory, or other sensory signal and is thought to reflect the speed of transmission of the central nervous system (Stelmach and Goggin, 1988). Experiments are conducted to measure the time it takes to initiate a response when an imperative stimulus is presented. The imperative stimulus is usually visual, but may be auditory or tactile. Such reactions can be to a single stimulus, multiple stimuli, or may include incompatible responses. In a simple reaction-time task, where one stimulus is given and one response is required, it has been demonstrated that reaction time increases in range from 0.5 ms/yr (5 ms/decade) (Fozard, Vercryssen, Reynolds, Hancock, and Quilter, 1994) to 2 ms/decade (Gottsdanker, 1982). It has been widely shown in the research that the speed of processing information decreases (i.e., the time increases) with advanced age on the order of 26 percent (264 ms in the young—20 years old—versus 327 ms in older adults—60 years old) (Welford, 1984). Similar findings have been reported for auditory and tactile simple reaction times as well (Redfern, Muller, Jennings, and Furman, 2002; Walhovd and Fjell, 2001; Liu, 2001; Walker, Alicandri, Sedney, and Roberts, 1991). This approximately 50-ms increase in simple reaction times is consistent across studies that have examined such changes across the life span (Fozard et al., 1994) as well as those that compare groups of young and older adults on the same reaction-time tasks (Amrhein, Stelmach, and Goggin, 1991; Walker, Philbin, and Fisk, 1997; Stelmach and Goggin, 1988; Cerella, 1985; Cerella, Poon, and Williams, 1980; Bashore, Ridderinkhof, and van der Molen, 1997; Gottsdanker, 1982; Stelmach and Goggin, 1988). See Schaie (in this volume) for a similar discussion of response speed with respect to cognitive changes that occur with advanced age.
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Technology for Adaptive Aging The slowing of processing speed in older adults is greater in tasks that require more complicated processing to initiate the appropriate response (Amrhein et al., 1991; Goggin and Stelmach, 1990; Larish and Stelmach, 1982; Stelmach, Goggin, and Garcia-Colera, 1987; Diggles-Buckles and Vercruyssen, 1990; Simon, 1967; Welford, 1977; Bashore et al., 1997; Cerella, 1985; Cerella et al., 1980; Fozard et al., 1994; Melis, Soetens, and van der Molen, 2002; Gottsdanker, 1982; Stelmach and Goggin, 1988). In a choice reaction-time task, subjects are required to select the appropriate response that corresponds to a specific stimulus. These reaction times are typically longer than in simple reaction-time tasks as they include an additional element of selecting the appropriate response. Older adults are 30-60 percent (50–500 ms) slower than young adults in reaction-time tasks with two to four choices (Amrhein et al., 1991; Simon, 1967; Welford, 1984; Jordan and Rabbitt, 1977; Stelmach and Goggin, 1988). Choice reaction time in older adults has been found to increase by 1.6 ms/yr and is amplified as the number of choices increases (Fozard et al., 1994). For example, in a two-, four-, and seven-choice reaction-time task, older adults were 39, 40, and 45 percent slower than young adults, respectively. Furthermore, older adults respond similarly to young adults: When the number of response choices increases, reaction time increases (Hick, 1952); however, the delays in responding are more substantial with multiple response choices. Some researchers have sought to decompose reaction time into premotor and motor time. Premotor time is defined as the time from the presentation of the stimulus until the onset of muscle activity and is thought to reflect cognitive processes, whereas motor time is the time from muscle activation to the beginning of the movement and reflects efficiency of the motor system. These studies have shown that most of the response delays in older adults are accounted for in the premotor or cognitive period (Clarkson, 1978; Hart, 1980; Spirduso, 1995). Further studies have decomposed the premotor cognitive processes into the time it takes to detect, prepare, and initiate an appropriate response. The majority of these studies have shown that the time utilized for each of these elementary components is prolonged equally in older adults (Simon and Pouraghabagher, 1978; Gottsdanker, 1982; Stelmach and Goggin, 1988; Stelmach et al., 1987, 1988). Collectively, the literature on response speed documents delayed initiation of a response in older adults compared with young adults across an array of simple and complex tasks. MOVEMENT CONTROL DECREMENTS Movement Duration Movement duration is defined as the time from the initiation of the movement to the termination of the movement (Birren, 1974; Salthouse,
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Technology for Adaptive Aging 1985). Movement time is increased in older adults for a variety of tasks including point-to-point movements (Amrhein et al., 1991; Cerella, 1985; Cooke, Brown, and Cunningham, 1989; Ketcham, Seidler, Van Gemmert, and Stelmach, 2002; Goggin and Meeuwsen, 1992), reaching and grasping movements (Carnahan, Vandervoort, and Swanson, 1998; Bennett and Castiello, 1994), handwriting (Amrhein and Theios, 1993; Dixon, Kurzman, and Friesen, 1993; Contreras-Vidal, Teulings, and Stelmach, 1998), and continuous movements (Greene and Williams, 1996; Pohl, Winstein, and Fisher, 1996; Wishart, Lee, Murdoch, and Hodges, 2000; Ketcham, Dounskaia, and Stelmach, 2001). Movement durations are on the order of 30-60 percent (50-90 ms) longer in older adults compared with young adults in tasks ranging from simple to complex (Welford, 1977); in extreme cases, slowing has been reported as great as 69 percent (421 ms compared with 132 ms in young adults) in a point-to-point movement (Stelmach et al., 1988). Although movement time is an important measure of how the motor system is performing, the effects observed vary greatly depending on the task. One common approach to assessing movement slowing is to manipulate task difficulty (information to be processed) in a stepwise fashion. Fitts′s law, a well-studied law in motor control research (Fitts, 1954), states that, as the difficulty of the movement increases, the speed of the movement decreases. A typical task would require the subject to move a hand as quickly as possible from a starting position to touch a target with a stylus when a “go” signal is given. The size of the target and the distance from the starting point to the target can be varied. The index of difficulty (ID) is greater for smaller targets and for longer movements. Research has shown that, in such tasks, older adults tend to move slower than young adults at all levels of difficulty but are differentially slower at higher levels of difficulty (Bashore, Osman, and Heffley, 1989; Goggin and Meeuwsen, 1992; Hines, 1979; Ketcham et al., 2002; Salthouse, 1988; Pohl et al., 1996; Walker et al., 1997; Brogmus, 1991; Fozard et al., 1994). For example, Ketcham and colleagues (2002) reported movement durations of a low ID to be 333 and 642 ms in young and older adults, respectively. At the higher ID, movement time of young adults was on average 717 ms compared with 1304 ms for older adults. Pohl and colleagues (1996) reported similar differences on a continuous movement task. Differences in movement times between young and older adults were amplified as task difficulty increased with an 80-ms time difference at the high ID compared with a 29-ms difference at the low ID. Task difficulty according to Fitts′s law can be manipulated in two ways: by a change in either the target size or the distance between the start and the end of the movement. When target size and movement distance are manipulated separately, researchers have demonstrated that older compared with younger adults
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Technology for Adaptive Aging are more affected by increases in movement amplitude (a change from 9.6 to 19.2 cm resulted in a 108-ms increase in movement time for young adults versus 293 ms for older adults) but not by decreases in target size (Ketcham et al., 2002; Goggin and Meeuwsen, 1992). Some authors have speculated that these effects are caused by the reduced ability of older adults to produce and maintain forces across the entire spectrum of the movement (Ketcham et al., 2002; Galganski, Fuglevand, and Enoka, 1993; Darling, Cooke, and Brown, 1989), which may have real-world implications on a variety of precision aiming tasks. Movement Components Modern data-acquisition techniques make it possible to record and reconstruct movements in real time, which permit investigators to decompose a movement trajectory to gain information on how a movement is controlled and coordinated. Trajectory profiles are processed to yield velocity and acceleration profiles, which are further decomposed into acceleration and deceleration phases as well as parsed into movement substructures. Experiments that have employed these kinematic analyses have provided insights into how the movements produced by older adults differ from those of young adults (Slavin, Phillips, and Bradshaw, 1996). It has been shown that the velocity profiles of young adults are typically bell shaped, where the acceleration phase equals the deceleration phase. In studies that have examined trajectory profiles of young and older adults, it has been observed that for older adults the trajectories are asymmetrical with a longer deceleration phase (Ketcham et al., 2002; Bennett and Castiello, 1994; Brown, 1996; Cooke et al., 1989; Darling et al., 1989; Goggin and Stelmach, 1990; Marteniuk, MacKenzie, Jeannerod, Athenes, and Dugas, 1987; Pratt, Chasteen, and Abrams, 1994). The deceleration phase has been suggested to contain the portion of movement that is under corrective control because there is sufficient time for sensory feedback to be processed and implemented into the control of the terminal phase of the movement. The deceleration phase in older adults is on the order of 20-40 percent longer than that of young adults (Brown, 1996; Cooke et al., 1989; Pratt et al., 1994; Bennett and Castiello, 1994; Morgan et al., 1994). In addition to longer deceleration phases, older adults produce movements with 30-70 percent lower peak velocity compared with young adults (Ketcham et al., 2002; Bellgrove, Phillips, Bradshaw, and Gallucci, 1998; Cooke et al., 1989; Goggin and Meeuwsen, 1992; Pratt et al., 1994) (see Figure 3-1). Furthermore, when movement distance increases, older adults do not increase the velocity of their movements to the same degree as young adults (Ketcham et al., 2002; Gutman, Latash, Almeida,
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Technology for Adaptive Aging FIGURE 3-1 Example velocity profiles for an older and a young adult on a point-to-point aiming task. SOURCE: Adapted from Ketcham et al. (2002, p. 56). and Gottlieb, 1993). For example, Ketcham and colleagues (2002) found that the peak velocity of a shorter-distance movement was 15.9 cm/s in older adults and 29 cm/s in young adults. When movement distance was increased from 9.6 to 19.2 cm, the peak velocity of older adults was 27.6 cm/s whereas for young adults it was 48 cm/s. Acceleration profiles can be partitioned into movement substructures (primary and secondary submovements) for a more in-depth analysis. The movement optimization model (Meyer, Abrams, Kornblum, Wright, and Smith, 1988) maintains that the primary submovement represents the portion of the movement under preplanned control where the limb is
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Technology for Adaptive Aging propelled to the target during the acceleration phase, whereas the secondary submovement represents the feedback-controlled portion of the movement. The closer to the target the primary submovement ends, the more efficient the motor system is thought to be (Meyer et al., 1988). Overall, research has demonstrated that older adults cover 10-70 percent less distance with their primary submovement compared with young adults, depending on the task (Bellgrove et al., 1998; Darling et al., 1989; Hsu, Huang, Tsuang, and Sun, 1997; Ketcham et al., 2002; Pratt et al., 1994; Walker et al., 1997; Romero, Van Gemmert, Adler, Bekkering, and Stelmach, 2003; Seidler-Dobrin, He, and Stelmach, 1998). Pratt and colleagues (1994) found that older adults covered 50 percent of the distance to the target with the primary submovement compared with young adults who traveled 70 percent of the distance (Figure 3-2). Because the primary submovement ends further from the movement end point, older adults need to make one or more adjustments with the secondary submovement to complete the movement accurately (Goggin and Meeuwsen, 1992; Hsu et al., 1997; Ketcham et al., 2002; Pohl et al., 1996; Pratt et al., 1994; Seidler-Dobrin and Stelmach, 1998; Walker et al., 1997). Researchers have extended the use of substructure analysis to assess how young and older adults differ in improving their movements with practice. Pratt et al. (1994) and Seidler-Dobrin and Stelmach (1998) demonstrated that both groups improved their movement times with practice, but they did it quite differently. Older adults only slightly increased (50 to FIGURE 3-2 Percentage of distance traveled in the primary submovement for older and young adults in a point-to-point aiming task over 10 blocks of 10 trials. SOURCE: Adapted from Pratt et al. (1994, p. 360).
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Technology for Adaptive Aging 51 percent) the portion of the movement covered with the primary submovement with 100 trials of practice whereas young adults increased the distance covered from 67 to 75 percent. These data, along with other studies that have used kinematic and movement subparsing techniques, have shown that the initial phases of the movement are similar in young and older adults, with older adults producing movements with lower peak velocity outputs. Conversely, these methods have shown marked differences in the terminal phase of the movement, measured by the deceleration phase, proportion of the movement covered in the primary submovement, and the subsequent secondary submovements, suggesting that older adults need to make corrective adjustments to their movement as they approach the target. Movement Variability Movement variability refers to an individual′s overall consistency of an executed task across trials. Increased variability may reflect decrements in the motor system in its ability to produce the same movement output repeatedly. There are two types of movement variability: variability of the end point and variability of the components of the movement trajectory. Over a wide variety of tasks, researchers report higher variability in the trajectory and end-point position of movements of older adults compared with young adults overall and when performance is examined in a more detailed trial-by-trial basis in a rapid aiming task (Brown, 1996; Cooke et al., 1989; Greene and Williams, 1996; Seidler-Dobrin et al., 1998; Ketcham et al., 2002; Darling et al., 1989; Welford, 1984; Abrams, Pratt, and Chasteen, 1998; Warabi, Kase, and Kato, 1984; Tedeschi et al., 1989). Walker et al. (1997) have shown that older adults have higher variability of end-point of their first submovement compared with young adults. For both young and older adults, as acceleration increased, the variability of end-point position also increased—however, at a significantly greater rate for older adults. Pratt and colleagues (1994) documented that older adults had higher end-point variability than young adults. Both young and older adults showed decreased end-point variability after extended practice; however, older adults did not improve as much as young adults. In addition to end-point analyses, researchers also have examined the variability of the movement trajectory using kinematic analysis techniques. Cooke and colleagues (1989) found that older adults were significantly more variable compared with young adults on measures including movement duration, peak velocity, and the acceleration/deceleration ratio. Furthermore, the variability of acceleration and deceleration increased differentially for older adults compared with young adults as the ampli-
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Technology for Adaptive Aging tude of the movement increased (Darling et al., 1989). Pratt et al. (1994) found that older adults showed higher variability in the distance traveled in the primary submovement that did not improve as much as young adults with extensive practice. It has been suggested that the irregularity of the amplitude and timing of muscle output in older adults is responsible for this overall increased variability in the trajectory of movements as well as variability of end-point position (Darling et al., 1989; Cooke et al., 1989; Brown, 1996; Goggin and Meeuwsen, 1992; Ketcham et al., 2002; Greene and Williams, 1996). Variability of executed movements on a moment-to-moment basis has large implications for daily activities of older adults. For example, if the motor system is quite variable, it is difficult to know whether you may knock over a glass when you reach for it. If you know you will always undershoot the glass, then you can plan for, prepare for, and compensate for that decrement. Speed and Accuracy Movements made to functional targets have a known speed-accuracy relationship. As individuals attempt to move faster, there is a point where the response accuracy is compromised. Individuals, based on their ability, often have different speed-accuracy behavioral patterns. The literature has shown that the reaction time and movement time of older adults are slower than those of young adults (see “Response Initiation” and “Movement Duration” above). One common observation of those investigators who have made cross-sectional comparisons is that older adults have a bias for accuracy at the expense of speed (Salthouse, 1985). Older adults are often more conservative with respect to speed than young adults (Salthouse and Somberg, 1982; Ketcham et al., 2002; Walker et al., 1997; Goggin and Meeuwsen, 1992; Darling et al., 1989). The question arises as to whether such differences are caused by changes in the neurophysiological factors or by different cognitive strategies. Do older adults purposely slow down their movements to ensure that they are made with a high level of accuracy? Most of the studies have attributed the observed slowing in movement control to physiological factors with only a few examining directly whether the speed-accuracy trade-offs actually exist (Salthouse, 1985; Bashore et al., 1989). Salthouse (1985) cited two studies that examined age differences in the speed-accuracy trade-off by manipulating the instructions or incentives that the subjects received for emphasizing speed or accuracy, respectively. Salthouse (1985) further states that both of these studies reported that adults of different ages have specific speed-accuracy characteristics, which show slower response speed as target accuracy becomes more precise, with older adults having slower re-
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Technology for Adaptive Aging sponse speeds than young adults at the same level of precision. Thus, age differences in relation to speed production, with an accuracy component, do exist independently of the subject′s emphasis on speed or accuracy. Therefore, in any study showing speed differences in cross-sectional age-group comparisons, the speed versus accuracy relationship should be determined. When an individual trades response speed for response accuracy, it is an example of the influence of cognitive processes on motor performance. Such cognitive strategies make it difficult to accurately determine the amount of change across age groups that is due to neurophysiological factors. This has significant implications for those who work with older adults. First, training programs should challenge older adults to move faster while maintaining accuracy. In addition, when assessing capabilities of older adults, it is important to give older adults more time to complete the task as they perform with accuracy levels similar to young adults when given enough time. Force Control and Regulation Force control is an elementary component of movement production because smooth and accurate movements require efficient modulation of force outputs. Changes in the regulation of force outputs lead to decrements in the initiation and control of movements. Older compared with young adults have decreased force outputs and inefficient force regulation making it difficult to initiate and execute movements quickly and accurately across a variety of tasks (Brown, 1996; Campbell, McComas, and Petito, 1973; Clamann, 1993; Cooke et al., 1989; Darling et al., 1989; Davies and White, 1983; Doherty, Vandervoort, and Brown, 1993; Galganski et al., 1993; Izquierdo, Aguado, Gonzalez, Lopez, and Hakkinen, 1999; Larsson and Karlsson, 1978; Milner-Brown, Stein, and Yemm, 1973; Milner, Cloutier, Leger, and Franklin, 1995; Roos, Rice, Connelly, and Vandervoort, 1999; Singh et al., 1999; Stelmach, Teasdale, Phillips, and Worringham, 1989). Stelmach and colleagues (1989), using an isometric task, demonstrated that older adults have a reduced range of force production and higher force output variability compared with young adults. In addition, their rate of force production was substantially slower, as it took 20 ms longer to achieve a force level 45 percent of their maximum (15 N). Ng and Kent-Braun (1999) documented similar findings with older adults. They reported 60-N lower peak force output in older adults compared with young adults and a 20-ms-longer time for force production. It has been shown that older adults produce multiple bursts of force in tasks when they must achieve targeted force levels approaching maximum (Kinoshita and Francis, 1996; Brown, 1996; Galganski et al., 1993).
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Technology for Adaptive Aging This is in contrast to young adults who produce a single burst to the targeted force level. Although these irregularities are small and occur over short periods, they do suggest a reason why control and coordination change with advanced age. Changes in force regulation and control have large implications for most functional tasks—for example, turning a door knob or picking up a glass of liquid. These changes may be a result of motor unit reorganization and muscle composition changes; see “Muscle Composition and Muscle Activation Patterns” below (Erim, Beg, Burke, and de Luca, 1999; Galganski et al., 1993; Hakkinen et al., 1996; Yue, Ranganathan, Siemionow, Liu, and Sahgal, 1999; Clamann, 1993; Davies and White, 1983; Milner-Brown et al., 1973). Coordination Coordination is the ability to control a number of movement segments or body parts in a refined manner resulting in a well-timed motor output. The ability to control multiple movement components at any one particular time becomes increasingly difficult with advanced age across a variety of movements including aiming, reaching and grasping, drawing, handwriting, and bimanual coordination tasks (Bennett and Castiello, 1994; Carnahan et al., 1998; Teulings and Stelmach, 1993; Greene and Williams, 1996; Swinnen et al., 1998; Wishart et al., 2000; Ketcham et al., 2001). For example in reach-to-grasp tasks, there are transport and grasp components that must be coordinated both spatially and temporally. Researchers have shown that older adults exhibit unstable temporal coupling between these components (Bennett and Castiello, 1994; Carnahan et al., 1998). Conversely, tasks such as drawing or handwriting that require subjects to control multiple joints in a linked segment have demonstrated that the joints involved require more regulation at fast movement speeds (Teulings and Stelmach, 1993; Ketcham et al., 2001). For example, Ketcham and colleagues (2001) found that in a cyclical drawing task older adults begin to distort their movements at 2.0 Hz (two cycles per second) compared with young adults who begin distortions at 2.5 Hz. It appeared that older adults were unable to accurately control the passive properties of linked segments, resulting in slower, more variable movements. Seidler and colleagues (2002) found that aiming movements away from the body, that required shoulder and elbow participation, became less smooth and decoupled as shoulder contribution increased (Figure 3-3). Furthermore, young adults tended to increase activity of opposing muscles as shoulder involvement increased, whereas older adults coactivated these muscles at high levels during single joint elbow movements and reduced coactivation as shoulder involvement increased.
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Technology for Adaptive Aging who maintain an active lifestyle show positive effects of exercise on the production of movement. Exercise training (both aerobic and strength) has also been shown to have general beneficial effects on strength and flexibility in older adults. It has been found that exercise training slows the adverse affects of aging even in those who start exercising as late as 80 years of age (Cress et al., 1999). Several studies have shown that light resistance training, stretching, and moderate aerobic exercise have a beneficial effect on strength, balance, flexibility, coordination, and range of motion in older adults (Raab et al., 1988; Fatouros et al., 2002; Gehlsen and Whaley, 1990; Girouard and Hurley, 1995; Drowatzky and Drowatzky, 1999; Morey et al., 1999). Strength training has been shown to have a specific impact on muscle composition and subsequent motor function. One of the major decrements in older adults is the change in composition of muscle. The decrease in muscle fibers, particularly type II muscle fibers (fast twitch), is largely associated with the lack of use. If the level of exercise training is maintained, the loss of muscle fibers is slowed or does not occur (Rogers and Evans, 1993; Frischknecht, 1998; Fielding, 1995). Weight training increases the number of type II fibers by 20 percent (Drowatzky and Drowatzky, 1999). It has also been shown that strength training increases maximum torque in plantar flexion movements in the feet, which are important for balance and mobility (Blanpied and Smidt, 1993). Increases in muscle mass and range of motion have been shown to reduce the risk of detrimental falls (Allander, Bjornsson, Olafsson, Sigfusson, and Thorsteinsson, 1974; Hortobagyi and DeVita, 1999; Pendergast, Fisher, and Calkins, 1993). Similar improvements have been found in dynamic balancing of older athletes with increased muscle mass and range of motion (Raty, Impivaara, and Karppi, 2002). Overall, the research shows that maintaining physical activity, including strength and flexibility training, slows the effects of aging on the motor system and may prevent some irreversible injuries or declines. Other data show more specific improvements in cognitive and motor function with specialized training. Kramer, Hahn, and Gopher (1999) have shown very specific benefits from training over several sessions on a dual-task paradigm. They showed that older adults, compared with young adults, have large time costs, measured by reaction time, when performing tasks that require switching of attention from one task to another. However, with modest practice, older adults were able to reduce the costs of switching between tasks. These improvements were maintained over a 2-month period. These data show that highly specialized training can improve a very specific kind of performance.
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Technology for Adaptive Aging Similar specialized training benefits have been shown with balance training interventions, particularly multifactor training (Daubney and Culham, 1999; Hu and Woollacott, 1994; Tang and Woollacott, 1996). Multifactor balance training requires several modalities of sensory information to be processed and integrated simultaneously. A review conducted by Tang and Woollacott (1996) found that multifactor balance training targeted to specific subsystems, working on individual needs, showed the most improvements in balance and postural responses. Training on a set of specific defined deficits in individuals resulted in improvements in stability and recovery from postural disturbances. Shumway-Cooke and colleagues (1997) have demonstrated that balance training programs that include tasks that involve multiple processes increase the attentional demands associated with balance control and become more like real-world experiences in which a person must respond to multiple inputs. Tasks such as maintaining balance while performing rhythmic movements between limbs increase the postural response resources available to individuals and subsequently improve compensatory strategies (Tang and Woollacott, 1998). Rose and Clark (2000) have reported that a biofeedback-based balance intervention improves balance control in older adults as measured by postural sway. Individuals who participated in biofeedback balance training were able to make quicker corrections to perturbations and able to recover from larger sway dispersions, suggesting more control of their center of gravity. Proprioception and gait training has also been observed to be beneficial to older adults to maintain balance (Gauchard, Jeandel, Tessier, and Perrin, 1999; Galindo-Ciocon, Ciocon, and Galindo, 1995). Overall, most available data that measure defined motor performance variables suggest that the benefits of intervention training are relatively specific. It needs to be determined whether more generalized intervention strategies such as exercise produce specific improvements in motor function such as speed, accuracy, coordination, and balance control. Another area that has begun to emerge, but needs to become the forefront of the field, is how technology can assist movement control and accuracy. There have been few studies that have shown the benefits of devices that improve the speed and accuracy of movements, as well as coordination and balance, in older adults. Maki and colleagues (1999) performed a study in which enhanced sensory inserts (raised edge around perimeter of foot) were put in the soles of subjects′ shoes. They found that this intervention improved the efficiency of stabilizing reactions elicited by unpredictable postural perturbations. This device targets improving balance control by enhancing sensation in the soles of individuals′ feet so that postural disturbances can be recognized and corrected before a detrimental outcome occurs. The results may be important in the design of
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Technology for Adaptive Aging assistive technologies to reduce instability and risk of falling in older adults. Technological advances in devices that assist older adults should target improving parameters of movement performance that have the largest impact on the skills of daily living. It is important for future technological advancements for older adults to incorporate and capitalize on the intact ability of older adults, while compensating for declines. This will lead to improvements in performance with training as well as help older adults maintain skills in which they are proficient. REFERENCES Abrams, R.A., Pratt, J., and Chasteen, A.L. (1998). Aging and movement: Variability of force pulses for saccadic eye movements. Psychology and Aging, 13(3), 387-395. Allander, E., Bjornsson, O.J., Olafsson, O., Sigfusson, N., and Thorsteinsson, J. (1974). Normal range of joint movements in shoulder, hip, wrist and thumb with special reference to side: A comparison between two populations. International Journal of Epidemiology, 3(3), 253-261. Amrhein, P.C., and Theios, J. (1993). The time it takes elderly and young individuals to draw pictures and write words. Psychology and Aging, 8(2), 197-206. Amrhein, P.C., Stelmach, G.E., and Goggin, N.L. (1991). Age differences in the maintenance and restructuring of movement preparation. Psychology and Aging, 6(3), 451-466. Aniansson, A., Hedberg, M., Henning, G.B., and Grimby, G. (1986). Muscle morphology, enzymatic activity, and muscle strength in elderly men: A follow-up study. Muscle and Nerve, 9(7), 585-591. Bailey, A.J., and Mansell, J.P. (1997). Do subchondral bone changes exacerbate or precede articular cartilage destruction in osteoarthritis of the elderly? [Review]. Gerontology, 43(5), 296-304. Bashore, T.R., Osman, A., and Heffley, E.F. (1989). Mental slowing in elderly persons: A cognitive psychophysiological analysis. Psychology and Aging, 4(2), 235-244. Bashore, T.R., Ridderinkhof, K.R., and van der Molen, M.W. (1997). The decline of cognitive processing speed in old age. Current Directions in Psychological Science, 6(6), 163-169. Bassey, E.J. (1998). Longitudinal changes in selected physical capabilities: Muscle strength, flexibility and body size. Age and Ageing, 27(Suppl 3), 12-16. Beaupre, G.S., Stevens, S.S., and Carter, D.R. (2000). Mechanobiology in the development, maintenance, and degeneration of articular cartilage. [Comment]. Journal of Rehabilitation Research and Development, 37(2), 145-151. Bell, R.D., and Hoshizaki, T.B. (1981). Relationships of age and sex with range of motion of seventeen joint actions in humans. Journal Canadien Des Sciences Appliquees Au Sport, 6(4), 202-206. Bellgrove, M.A., Phillips, J.G., Bradshaw, J.L., and Gallucci, R.M. (1998). Response (re-) programming in aging: A kinematic analysis. Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 53(A3), M222-M227. Bennett, K.M., and Castiello, U. (1994). Reach to grasp: Changes with age. Journal of Gerontology, 49(B1), P1-P7. Berardelli, A., Hallett, M., Rothwell, J.C., Agostino, R., Manfredi, M., Thompson, P.D., and Marsden, C.D. (1996). Single-joint rapid arm movements in normal subjects and in patients with motor disorders. Brain, 119, 661-674. Bernick, S., and Cailliet, R. (1982). Vertebral end-plate changes with aging of human vertebrae. Spine, 7(2), 97-102.
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Representative terms from entire chapter: