Biomechanics of reaching: Clinical implications for individuals with acquired brain injury

Abstract

Purpose

Outline the biomechanics of reaching both in healthy individuals and in individuals with acquired brain injury (ABI), and to discuss the clinical implications for using valid biomechanical models to assess reaching.

Methods

A review of current literature, including a MEDLINE search using keywords of reaching, acquired brain injury, stroke, biomechanics and motor control.

Results

Current assessments of the upper extremity in acquired brain injury (ABI) are focused on single joint characteristics of range of motion, strength, and spasticity. However, reaching is a functional multijoint task requiring interjoint coordination in addition to feedback and feedforward control to optimally position the hand at a desired location so that it may interact with the environment. From the literature, biomechanical measures of reaching such as movement time, movement distance and interjoint coordination have been shown to discriminate changes to hand path quality following brain injury. These measures also have been shown to correlate with measures of sensorimotor function (e.g., Fugl-Meyer) in the upper extremity.

Conclusions

Further development of reliable and valid multijoint biomechanical evaluations is required, particularly for natural and goal-oriented reaching movements. The biomechanical assessment of reaching in ABI can provide an understanding of the specific deficits in physiological structures or motor planning underlying altered reaching ability, assist in the evaluation of new therapies, and characterize the recovery process following ABI.

1. Introduction

The ability to reach is critical for virtually all activities of daily living such as grooming, toileting, feeding, transfers, and dressing.¹ Reaching has been defined as the voluntary positioning of the hand at or near a desired location so that it may interact with the environment.² It requires coordination of multiple joints and involves both the musculoskeletal and neural systems. Although grasping³ and postural control⁴ actions often accompany a reach, these elements are controlled by distinct motor programs.⁵ For the purpose of this review, we will restrict our discussion to the reaching process alone.

Patients with stroke and traumatic brain injury (TBI) suffer high rates of impairment to the upper extremity with approximately 85% incurring acute impairment and 40% incurring chronic impairment.⁶ In over half of individuals with a stroke, the affected upper extremity remains severely impaired despite intensive and prolonged rehabilitation.⁷ Furthermore, in both stroke and TBI patients, the upper extremity recovers less than the lower.⁸ Stroke patients rate return of upper extremity function as a high priority⁹ and failure to substantially recover upper limb function can lead to depression and withdrawal.¹⁰

Reaching ability following an ABI is generally assessed on an ordinal scale as one component of a standardized upper extremity function scale, e.g., Frenchay Arm Test.¹¹ These global scales are useful for measuring gross changes in functional performance but lack sensitivity to small yet important changes. Furthermore, ordinal scales provide little information as to the underlying causes of the motor dysfunction. A full understanding of human movement requires the integration of kinematic (movement) and kinetic (force) analyses to identify the internal forces (e.g., from muscles, ligaments) and external forces (e.g., from contact with an object such as a door or from a load such as a fork) acting upon the body.^12–14 Electromyography, kinematic, and kinetic measures during movement are sensitive to the effects of neurological and orthopaedic conditions and their treatments.^15,16

Movement analysis of reaching can identify changes in interjoint coordination or the quality of the hand path (e.g., directness, smoothness) following brain injury. In fact, kinematic measures of movement time, movement distance and interjoint coordination during a reaching task are strongly correlated to functional measures of upper extremity function (e.g., Fugl-Meyer upper extremity score) in individuals with stroke.¹³ Kinematic and kinetic measures can be used not only to assess performance but also to elucidate the motor strategies used during a goal-oriented reach. In addition, movement analysis of reaching may be useful for the evaluation of existing¹⁷ and developing upper extremity therapies in acquired brain injury (ABI) such as the force use paradigm where the less affected arm is restrained to encourage use of the more affected extremity,¹⁸ the use of neuromuscular blocks (e.g., botulinum toxin) to upper extremity muscle to relieve spasticity,¹⁹ and robotic assisted reaching exercises.²⁰

Despite the fact that reaching is one of the major functions of the upper extremity and has poor recovery in ABI,⁶ the biomechanics of this multijoint task are largely ignored in undergraduate rehabilitation curriculums relative to the emphasis placed upon the multijoint function of the lower extremity. Therefore, the purposes of this paper are (1) to outline the biomechanics of reaching in healthy individuals, (2) to review the uses of current clinical assessments of reaching function in ABI, (3) to describe the findings of biomechanical investigations in ABI, and (4) to discuss the clinical implications and future considerations for the use of valid biomechanical models for the assessment of reaching. We performed a systematic literature search and based on a MEDLINE search using the keywords “reaching”, “acquired brain injury”, “stroke”, “biomechanics” and “motor control”. Additional references were gleaned from the articles identified.

2. Biomechanics of Normal Reaching

Reaching to a target within arm’s length involves the shoulder, elbow, and wrist. Reaching to targets beyond arm’s length involves movements at all these joints, as well as trunk and hip motion.²¹ These joints work together as a coordinated mechanical system in healthy individuals to accurately place the hand in a desired position. Understanding the biomechanical and neuromotor control processes underlying reaching in the healthy population can help clinicians to identify where deficits may occur in persons with ABI.

Segments of the upper limb may move about seven possible degrees of freedom (DOF) (i.e., joint rotations), in the shoulder (3 DOF), elbow (1 DOF), forearm (1 DOF) and wrist (2 DOF), in addition to elevation/depression and protraction/retraction of the shoulder-scapular complex. This natural excess of joints affords the central nervous system (CNS) the ability to employ an infinite number of paths and when reaching to a specific target. Despite the many available degrees of freedom, joint motion during reaching is similar for a given start position, end position, and hand orientation across the healthy population.^21,22 Functionally, the redundancy of joints provides the ability to adaptively and optimally control movements to account for internal and external environmental factors²³ such as compensating for an injury or altering the hand trajectory to avoid collision with an object.

Neuromuscular control of reaching is computationally complex and requires the synchronization of muscle activation at all the moving joints as well as all the muscles involved in postural stabilization. The acceleration of each joint during a reaching movement depends upon both the net joint torque (i.e. rotational force) and inertia (resistance of an object to any change in motion); rotational inertias experienced by upper extremity joints are coupled by the movements and configurations of the upper arm, forearm, and hand.²⁴ The net joint torque is due not only to muscle activity but also to the effects of gravity, joint viscoelasticity, and externally applied forces (e.g. the reaction force of a door on the hand as it is being opened). Gravitational effects depend upon the weight and general orientation of the arm segments. Viscoelasticity is the inherent mechanical property of passive tissues (i.e. muscles and tendons) to stabilize joint position.

The central nervous system (CNS) planning of reaching movements may be considered as a hierarchical control in which spatial information is converted to motor patterns at the shoulder and elbow to move the hand through space. A series of transformations convert sensory signals into hand trajectories, then into corresponding joint trajectories, required muscular torques, and finally into the actual patterns of muscle activity.²⁵ While there is general agreement regarding this motor control process, there are debates over the specific coordinate system used in planning reaching movements and whether or not the muscle torques are explicitly represented by the CNS.²⁶ For example, some have suggested that at the highest level, planning could occur in terms of a joint angle co-ordinate system (e.g., control of shoulder, elbow and wrist angles)²⁷ or in terms of the final endpoint co-ordinates (i.e., target).²⁸

The CNS uses both feedforward and feedback strategies to control reaching movements.⁵ The first phase of reaching is feedforward (preplanned) controlled, sensory information is used to anticipate disturbances to limb dynamics and plan appropriate muscle activation based on experience. Feedforward control is characterized by a profile of continuous movement that contains one acceleration and one deceleration phase. The second phase of reaching is feedback controlled and corrects for discrepancies between where and how one wants to place the arm versus the current position and speed of the arm. In feedback control, signals from peripheral receptors provide information back to the nervous system about the events occurring in the muscles, joints and other tissues. Feedback control is characterized by a profile of discontinuous movement that contains multiple accelerations and decelerations of progressively shorter duration as the error between the hand and the target approaches zero.²⁹ Control of voluntary movements improves with practice as we learn to anticipate and correct for disturbances resulting from internal and external forces acting on the body.³⁰ People of all ages exhibit this ability to adapt their reaching strategies to changing environmental and physiological factors.³¹

Normal multijoint reaching is characterized by a smooth bell shaped velocity profile with a peak velocity approximately halfway between the start and endpoints (see line LA in Figure 1). The peak velocity corresponds to the changeover from the acceleration and deceleration phases and its location within the velocity profile is an indicator of strategy. As requirements for accuracy increase, the bell shaped velocity profile becomes skewed and the peak velocity occurs earlier in movement. Conversely, as requirements for speed increase, the peak velocity occurs later in movement. The relationship between movement speed and accuracy during reaching movements is known as Fitts’ law³² where an increase in accuracy (decreasing the target width) is related to a reduction in reaching speed.

Figure 1.

Fingertip speeds for the more affected (MA) and less affected (LA) arms while during a reaching task. The subject (SR01: age = 57, injury = hemorrhagic stroke affecting the right side, time since stroke = 6 years, Fugl-Meyer upper extremity function = 19/66) was seated with a belt across the chest to restrain trunk movement. An auditory tone cued the subject to reach from a start position on the mid thigh to a target at shoulder height as “fast as possible”. The speed profile of the MA arm is less symmetric and more segmented than the LA arm.

Hand paths during reaching movements are straight or slightly curved.²⁸ Producing such a path requires a subject to coordinate rotations of both shoulder and elbow joints, typically characterized by a roughly constant ratio of joint angular velocities.^33,34 A measure of the straightness of the hand path (known as the hand directness) is the ratio of the actual path length to that of the direct path.³⁵ Straight hand paths require simultaneous rotation of the elbow and shoulder so that inter-joint coordination in healthy individuals is demonstrated by a near constant ratio of the elbow and shoulder angular velocities throughout the reaching movement.^33,34 Deviations from straight line paths is caused by reduced coordination of the shoulder and elbow joint movements. Analyses of interjoint coordination may be helpful in understanding the nature of movement deficits in individuals with CNS lesions.^36,37

3. Upper Extremity Assessments in ABI

Reaching may be affected by a number of impairments following an ABI, including spasticity, a decreased range of motion (ROM), coordination difficulties and weakness resulting from peripheral muscle atrophy or decreased central motor recruitment.³⁸

Weakness from either peripheral (e.g., muscle atrophy) or central sources (e.g., reduced motor unit recruitment) may be the major impairment underlying the functional disability of the more affected upper limb in ABI injury.^38–40 Classifying muscle strength by manual testing⁴¹ has limited sensitivity to strength deficits in ABI.⁴² Muscle strength is better measured using hand held dynamometry, which is sensitive to low and high levels of force^43,44 and is a reliable⁴⁵ and valid⁴⁶ measure of hemiparetic muscle strength.

Spasticity is one of the principal factors affecting rehabilitation⁴⁷ following an upper motor neuron lesion (UMN). Spasticity has been defined as a velocity dependent increase in the tonic stretch reflex.⁴⁸ The sensation of resistance while moving the joint passively through its range of motion, and the degree of resistance is one manifestation of spasticity that is commonly assessed using the Ashworth scale.^49,50 The 5-point modified Ashworth scale has a high inter-rater reliability for an extension movement of the elbow joint⁵⁰ but tends to cluster scores in the middle range rendering the scale insensitive to subtle changes that may result from treatment.^51,52 There is growing recognition that tone is only one dimension of spasticity as spasticity can also manifest in contractures, reduced active joint range, muscle spasms, pain, heterotopic ossification, and clonus.^53,54

Isolated joint measurements of weakness under isometric loading and spasticity in passive motion may not be functionally significant. Reaching tasks are inherently multijointed and require the integration of musculoskeletal and neural components. The relationship between single joint assessments and reaching is largely undetermined. The effect that these impairments may have on reaching can be better understood in the context of an integrated model of the neuromuscular system. Such models have been well used in simulating reaching movements in the healthy population.⁵⁵

Consider the process of initiating and completing a reaching movement using a spastic hemiparetic arm in a simple model that we propose (Figure 2). Once a target is specified, the feedforward controller (A) generates patterns of muscle activation that are used to drive agonist muscles (B) (e.g., triceps brachii). However, decreased motor recruitment and disuse atrophy may limit the forces that agonist muscles can generate. As the hand moves towards the target, elbow extension and shoulder flexion may be restrained by increases in tone. Increased tone may be due to structural changes in muscles that result in elevated viscoelasticity (C). Increased tone may also be due to hyperreflexia (increased sensitivity to muscle receptor stretching) (D), which causes antagonist muscles (e.g., biceps brachii) (E) to contract.⁵² The resultant forces from muscle contractions, the environment, gravity (F), and viscoelasticity in addition to the inertias of the arm (G) determine the accelerations of the upper arm and forearm. If the original motor command does not adequately compensate for arm dynamics, the hand may not reach the desired target. New positions of the hand and joints will be detected by the sensory system (H) and iteratively corrected by the feedback controller (I).

Figure 2.

Simple model of the neuromuscular system applied to a spastic hemiparetic arm during forward reaching. Junctions that sum or compare signals are represented by “⊗”. Agonist and antagonistic muscles are indexed to m and n respectively. Reaching impairment could arise at various components of the model, eg. inability to activate muscles due to decreased motor recruitment (A & I), inability to generate muscle force due to disuse atrophy (B), changes in muscle structure that result in increased viscoelasticity (C), and increased gain (sensitivity) to stretching of muscle receptors (hyperreflexia) (D).

Task-based instruments for the upper extremity, e.g. Action Research Arm,⁵⁶ Frenchay Arm Test,¹¹ Peg Tests,⁵⁷ Rivermead Motor Assessment,⁵⁸ and Motor Assessment Scale⁵⁹ score function on a “can” or “cannot” basis. In addition to the lack of sensitivity to partially completed movements, these assessments fail to provide valuable information about the strategies and mechanisms underlying abnormal reaching. These instruments are only concerned with the ability to achieve a preset goal, treating all the physiological structures and possible impairments as a black box. A more comprehensive assessment is the upper extremity component of the Fugl-Meyer Scale,⁶⁰ which is composed of ordinal scales for sensation, proprioception, joint pain, and range of motion (shoulder, elbow, wrist and fingers), reflex activity, and joint coordination. The Fugl-Meyer Scale has a high inter-rater reliability.^61,62 However, its individual test components neither assess purposeful reaching tasks nor quantify the functional impairments due to spasticity or weakness.

4. Biomechanics of Reaching in ABI

Although biomechanical analyses have been used to identify reaching characteristics in healthy individuals, basic principles such as Fitts’ Law have yet to be evaluated in individuals with brain injuries during functional reaching tasks.

Krebs et al.⁶³ used kinematic analyses of hand paths to track the recovery pattern and identify adaptive strategies during unconstrained reaching tasks following brain injury. They found an improvement in twenty stroke survivors of acute stroke in both accuracy and smoothness in reaching movements and drawing tasks and the re-acquisition of bell-shaped velocity profiles over an 11 week period following their strokes. In addition, improvements of hand velocity in reaching during the acute period following stroke have also been reported.^64,65

Kinematic analyses of hand paths have produced evidence that persons with chronic stroke may select a strategy that optimizes their environment and neuromuscular system.^66–68 Trombly⁶⁸ found that the kinematic profile of the non-paretic arm during reach is fast and continuous whereas the profile of the paretic arm is slow and discontinuous. She suggested that the CNS adapts a feedback control in the paretic arm to correct deviations from the desired trajectory. We have found in our lab (unpublished findings) that the reaching kinematics of the spastic hemiparetic arm is more segmented and less symmetrical than the healthier arm (see line MA in Figure 1). Roby-Brami⁶⁷ tested reaching to cone shaped targets in the horizontal plane and found that individuals with chronic stroke selected strategies that compensated for their specific impairments; those with predominantly proximal impairments slid their hands along a supportive table while patients with predominantly distal impairments made downward stabs. Cirstea and Levin⁶⁶ found that patients with moderate and severe impairments in the paretic arm would involve trunk movements to targets that were within arm’s length and that the recruitment of an extra degree of freedom may be related to the severity of the impairment.

Goal-directed actions seem to produce significantly smoother and faster reaching movements of the non-paretic arm in persons with chronic stroke than “no object” conditions.⁶⁹ Moreover, practically preferred and meaningful targets such as food items have resulted in even faster and smoother movements.⁷⁰ This suggests that movement efficiency may be enhanced in therapy and assessment by using functionally significant target objects during goal oriented reaching.

Elbow and shoulder coordination has been investigated in individuals with stroke using a reaching task in the horizontal plane with the arm supported by a table. During these tasks, kinematic measures of interjoint co-ordination (ratio of the shoulder-elbow velocity) were more strongly correlated with impairment as measured by the Fugl-Meyer test than with spasticity scores.¹³ In addition, it has been suggested that individuals with stroke lack the required compensation for inertial torques (i.e., torques dependent upon movements from other joints) during fast reaching movements and consequently result in larger deviations between the initial direction of reaching movement and the actual target direction.^71,72 These directional errors are associated with excessive rotation of the elbow with respect to the shoulder. Beer et al.^71,72 suggested that the inability of patients to specify joint co-ordination may be partly due to decreased ability to predict limb dynamics in feedforward control.

Elbow and shoulder coordination has also been investigated using reaching tasks in which the hand path is physically restricted to straight paths of specified direction (e.g., forward/backward, lateral/medial). These constrained tasks can provide complementary information to unconstrained natural movements. If the elbow and shoulder joints act in a coordinated fashion during a constrained task, the hand will accelerate towards the target. However, in individuals with stroke, altered coupling of the elbow and shoulder joints results in forces acting in directions other than the intended direction.^14,15,73 These forces, known as constraint forces, can differentiate between the pathological extensor and flexor synergies found in ABI (as defined by the Fugl-Meyer scale).⁷³ The magnitude of these constraint forces increases when reaching movements are exerted against greater gravitational loads (e.g., reaching in increasingly upward directions).^14,73

A constrained reaching task was also used to investigate the multijoint effects of tone by measuring the resistive force when the upper limb is passively extended into a reach position and moved at a slow enough rate to avoid excitation of stretch reflexes and inertial effects.^14,73 The force required to hold the arm in an extended position was consistently higher in the paretic arm when compared to the non-paretic arm.^14,73,74 Joint torque analysis indicated that this increase was due to muscle or joint based contractures at both the shoulder and elbow.^14,73–75 Although a constrained reaching paradigm can characterize passive and active mechanical properties of the upper limb, predefined paths may not represent naturally occurring unconstrained reaching movements.⁷⁶

Results from constrained reaching assessments have shown that spastic reflexes are not elicited at speeds found in normal reaching.⁷³ Furthermore, stretch responses when the muscle is activated are comparable between the paretic and non-paretic arms.^14,73 Together, these studies suggest that the inability of persons with spastic hemiparesis to extend their arm in a reaching motion is primarily related to agonist muscle weakness and not restraint from spastic antagonist muscles.^14,73

5. Clinical Utility of Biomechanical Assessments and Models

The use of biomechanical analysis techniques in assessing patients with ABI is still in its infancy, and much remains to be done to develop these techniques. The development of multi-joint biomechanical evaluations of natural and goal-oriented reaching movements is required. The majority of biomechanical evaluations performed to date involve reaching movements performed at one speed in the horizontal plane with the arm supported. We need to evaluate the effects of different reaching conditions in ABI such as speed, effect of gravity (e.g., reaching upwards or downwards), accuracy, direction and sitting posture.

Kinematic and kinetic descriptions of reaching in the affected arm have indicated that hand paths become less smooth and rotations at the elbow and shoulder become less coordinated as targets progressively move farther contralateral, upwards, and forwards.^13,14,73 The effect of this increasing taxation on the motor system could be used to develop a biomechanically valid hierarchical performance assessment of reaching in which targets are placed in increasingly more difficult locations. Such assessments would likely be more valid if functionally relevant objects (e.g., cups) were used as targets.^60,70 In addition, there needs to be further study of the reliability and validity of biomechanical parameters of reaching ability. These investigations have been initiated and the results are promising; measures of force magnitude and directional error during a reaching task in chronic stroke exhibited moderate to high test-retest reliability and measures of directional force error in the more affected arm were a valid and sensitive measure of impairment when correlated with Fugl-Meyer upper extremity assessments.¹⁵

Most current upper extremity assessments focus on measures (e.g., ROM, spasticity, strength) across a single joint and there is little information as to how these clinical findings relate to multijoint functional reaching ability. Since the complex devices required to evaluate multijoint reaching are not likely to soon make the transition from research to clinical settings, it is important to establish the relationships and develop valid models between single joint and multijoint assessments. Such models have proven useful in relating muscle strength to multijoint lower extremity gait performance.^77,78

The biomechanical studies of reaching have demonstrated the importance of variables not traditionally evaluated in rehabilitation, such as hand path and movement speed that could be integrated into traditional clinical assessments. In fact, observational kinematic assessments of upper limb movements have shown that therapists using visual analogue scales are capable of making accurate judgments of movement speed (r>=0.87), jerkiness (r>=0.78), and hand path indirectness (r>=0.68) when compared to kinematic assessments using computerized video systems.⁷⁸

Finally, biomechanical studies of a reaching task have identified specific deficits in upper extremity function that could direct future clinical studies. For example, reaching performance is not likely related to antagonist muscle spasticity but to agonist muscle weakness and the inability to transform desired hand trajectories into coordinated elbow and shoulder joint movements.^13,14,73 Therapeutically, this suggests that improved reaching function may result from strength training and the restoration of normal sensorimotor relationships between joints^13,14,73 through practice.²⁰ Thus, future clinical studies need to test these hypotheses that are based on sound biomechanics.

In conclusion, biomechanical assessments of a reaching task can play a complementary role to current clinical assessments to provide an understanding of the mechanisms underlying altered reaching ability following ABI.