Integration of proprioception in upper limb prostheses through non-invasive strategies: a review

Abstract

Proprioception plays a key role in moving our body dexterously and effortlessly. Nevertheless, the majority of investigations evaluating the benefits of providing supplemental feedback to prosthetics users focus on delivering touch restitution. These studies evaluate the influence of touch sensation in an attempt to improve the controllability of current robotic devices. Contrarily, investigations evaluating the capabilities of proprioceptive supplemental feedback have yet to be comprehensively analyzed to the same extent, marking a major gap in knowledge within the current research climate. The non-invasive strategies employed so far to restitute proprioception are reviewed in this work. In the absence of a clearly superior strategy, approaches employing vibrotactile, electrotactile and skin-stretch stimulation achieved better and more consistent results, considering both kinesthetic and grip force information, compared with other strategies or any incidental feedback. Although emulating the richness of the physiological sensory return through artificial feedback is the primary hurdle, measuring its effects to eventually support the integration of cumbersome and energy intensive hardware into commercial prosthetic devices could represent an even greater challenge. Thus, we analyze the strengths and limitations of previous studies and discuss the possible benefits of coupling objective measures, like neurophysiological parameters, as well as measures of prosthesis embodiment and cognitive load with behavioral measures of performance. Such insights aim to provide additional and collateral outcomes to be considered in the experimental design of future investigations of proprioception restitution that could, in the end, allow researchers to gain a more detailed understanding of possibly similar behavioral results and, thus, support one strategy over another.

Keywords: Non-invasive feedback; Proprioception; Prosthetics; Upper-limb amputation.

Fig. 1

Graphic comparison between physiological and artificial transduction of proprioceptive information. The outer columns show how the function of the receptors in our body (left) could be emulated by some of the common sensors already available on the market (right). In prosthetics, the employed hardware dictates the strategies to be implemented (inner columns) and the input signal may differ from the one coded by the physiological receptor. For instance, the number of cycles of the motors extracted by rotary encoders is used instead of the muscle length, while the current to the motors may replace tendon tension, as an alternative to a tension sensor, which is less common and would need to be purposefully integrated into the device additionally

Fig. 2

Acquiring and encoding proprioceptive info for sensorimotor integration in prosthetics. 1. The actuator of the prosthesis operates the end effector based on the uptaken biologic signals of the user (e.g., EMG activity through surface electrode in case of myoelectric devices); 2. Sensors embedded in the prosthesis extract the configuration and power developed by the device (e.g., the joint angle is uptaken by the rotary encoders, pressure by superficial sensors and the force exerted is derived from the current adsorbed by the motors), also accordingly with the interaction with the environment (e.g., the cup grasped); 3. Data acquired from the sensors, which refer to proprioceptive-like parameters characterizing the state of the device are translated into feedback content to be delivered to the user; 4a. The feedback content is encoded back into input signals for the stimulators, on the basis of the amount of information to be transmitted, as well as the hardware’s capacities; 4b. The prosthesis, if implemented, can automatically modify (reflex-like behavior) the motor output based on the uptaken data; 5. The stimulators integrated into the device socket deliver the information to the sensory channels available in the stump or elsewhere (e.g., skin-stretch and electrotactile stimuli to skin mechanoceptors and nerve free endings respectively); 6. Once learnt how to interpret the flow of afferent information, the user is able to infer size, shape and stiffness of the object held by combining, for example, the information relative to prosthetic hand aperture and force developed; 7. Such information can be used consciously or unconsciously to correct the new motor command (e.g., increase muscle contraction) without constantly looking at the device, thus freeing attentional resources

Fig. 3

Examples of proprioception restitution strategies for coding positional and movement-related information. Stimulation devices have been illustrated as applied to a single limb to simulate their simultaneous use, but their choice will inevitably depend on the user’s level of amputation and will therefore be tailored to the individual. The degree of grip aperture has been encoded into the movement of a skin-stretch stimulation device, whose position on the user’s skin can be employed to infer the state of the prosthetic hand, thereby reducing the need for careful vision inspection [73]. Also, the prosthetic wrist’s prono-supination state has been fed back by activating a dedicated combination of electrodes on the user’s forearm [86]. Vibrotactile motors around the arm of the user have been used to encode discrete angular positions of the controlled myoelectric elbow [87]

Fig. 4

Examples of proprioception restitution strategies integrating both kinematic senses of position and movement and sensation of force. Stimulation devices have been illustrated all together, although the choices of the devices as well as eventual combinations must be tailored to the individual’s needs. Electrotactile arrays can be used to provide different types of information by means of multiple encoding strategies: for instance, discrete grasping angles, corresponding to specific couples of electrodes on the user’s forearm can be conveyed through spatial coding. Additionally, the frequency of the electrotactile stimulus provided by the last pair of electrodes can be proportionally adjusted to reflect the grasping force measured at the tips of the prosthetic fingers [104]. Using a different approach, the amplitude of a vibrotactile stimulus on the user’s forearm was set proportional to the grip’s closing velocity [105]