| Literature DB >> 32213196 |
Javier Gil-Castillo1, Fady Alnajjar2, Aikaterini Koutsou1, Diego Torricelli1, Juan C Moreno1.
Abstract
This paper reviews the technological advances and clinical results obtained in the neuroprosthetic management of foot drop. Functional electrical stimulation has been widely applied owing to its corrective abilities in patients suffering from a stroke, multiple sclerosis, or spinal cord injury among other pathologies. This review aims at identifying the progress made in this area over the last two decades, addressing two main questions: What is the status of neuroprosthetic technology in terms of architecture, sensorization, and control algorithms?. What is the current evidence on its functional and clinical efficacy? The results reveal the importance of systems capable of self-adjustment and the need for closed-loop control systems to adequately modulate assistance in individual conditions. Other advanced strategies, such as combining variable and constant frequency pulses, could also play an important role in reducing fatigue and obtaining better therapeutic results. The field not only would benefit from a deeper understanding of the kinematic, kinetic and neuromuscular implications and effects of more promising assistance strategies, but also there is a clear lack of long-term clinical studies addressing the therapeutic potential of these systems. This review paper provides an overview of current system design and control architectures choices with regard to their clinical effectiveness. Shortcomings and recommendations for future directions are identified.Entities:
Keywords: Foot drop syndrome; Functional electrical stimulation; Gait; Neuroprosthetics
Year: 2020 PMID: 32213196 PMCID: PMC7093967 DOI: 10.1186/s12984-020-00668-4
Source DB: PubMed Journal: J Neuroeng Rehabil ISSN: 1743-0003 Impact factor: 4.262
Fig. 1Biomechanics of the ankle in the gait cycle, musculature and nerves. The graphs represent the biomechanics of the ankle of a healthy subject (black continuous line) versus the biomechanics of a subject with foot drop (red segmented line). An example of muscle activity in foot drop (taken and adapted from [3]) is plotted in panel D (red)
Fig. 2Flow diagram for procedure followed
Fig. 3Architecture of a FD neuroprosthesis. This figure shows the sensors that have been used in the last two decades, as well as their location on the body. It also details the stimulation parameters and where assistance is normally applied
Foot drop FES systems
| Devices | Sensors | Transcutaneous/Implanted | # of Channels | Assistance | Muscles/nerves |
|---|---|---|---|---|---|
| Haugland et al. [ | FSRs | Implanted | 2 | Dorsiflexion | Peroneal nerve |
| Kottink et al. [ | FSRs | Implanted | 2 | Dorsiflexion, eversion | Peroneal nerve |
| ShefStim [ | FSRs | Transcutaneous | 64 | Dorsiflexion, eversion | Multiple muscles |
| Perumal et al. [ | FSRs | Transcutaneous | 2 | Dorsiflexion and plantarflexion | Flexor-extensor muscles |
| Sabut et al. [ | FSRs | Transcutaneous | 2 | Dorsiflexion | Peroneal and anterior tibial nerve |
| ExoStim [ | Inertial | Transcutaneous | 8 | Dorsiflexion | Unspecified |
| BIONic WalkAide [ | Tilt sensor | Implanted | 1 | Dorsiflexion | Tibialis anterior and peroneal nerve |
| Ismail et al. [ | Inertial | Transcutaneous | 2 | Dorsiflexion | Peroneal nerve |
| Watanabe et al. [ | Inertial | Transcutaneous | 1 | Dorsiflexion | Tibialis anterior and peroneal nerve |
| Compex Motion [ | FSR + Inertials | Transcutaneous | 4 | Dorsiflexion | Tibialis anterior and peroneal nerve |
| Gait MyoElectric [ | FSRs + Inertials | Transcutaneous | 2 | Dorsiflexion and plantarflexion | Flexor-extensor muscles |
| Runbot III and II [ | FSRs + Inertials | Transcutaneous | 8 | Dorsiflexion and plantarflexion | Tibialis anterior, lateral gastrocnemius, biceps femoris and rectus femoris |
| Do et al. [ | EEG | Transcutaneous | 2 | Dorsiflexion | Peroneal nerve |
| NeuroStep [ | Neural clamps of electrodes | Implanted | 2 | Dorsiflexion and plantarflexion | Tibialis anterior and peroneal nerve |
| Chen et al. [ | FSRs | Transcutaneous | 1 | Dorsiflexion | Tibialis anterior muscle |
| DeltaStim [ | FSRs | Transcutaneous | 2 | Dorsiflexion and eversion | Peroneal and anterior tibial nerves |
| APeroStim [ | FSRs | Transcutaneous | 2 | Dorsiflexion, eversion and inversion | Tibialis muscle and fibularis longus |
| Duo-STIM [ | FSRs + Inertials | Transcutaneous | 2 | Dorsiflexion | Unspecified |
| Li et al. [ | EMG | Transcutaneous | 2 | Dorsiflexion | Tibialis or medial gastrocnemius muscles |
| RehaMove Pro [ | Inertial + EMG | Transcutaneous | 4 | Dorsiflexion | Unspecified |
| Nahrstaedt et al. [ | Electrodes to measure bioimpedance | Transcutaneous | 4 | Dorsiflexion | Dorsiflexors muscles |
| O’Keeffe et al. [ | FSRs, Inertials, EMG and electrogoniometers | Unspecified | 2 | Dorsiflexion | Unspecified |
| Melo et al. [ | FSRs + Inertials | Transcutaneous | 2a | Dorsiflexion and plantarflexion | Flexor-extensor muscles |
| MyGait [ | FSRs | Transcutaneous | 2 | Dorsiflexion | Peroneal nerve |
| Odstock [ | FSRs | Transcutaneous | 1 | Dorsiflexion | Unspecified |
| NESS L300 [ | FSRs | Transcutaneous | 2 | Dorsiflexion | Tibialis anterior and peroneal nerve |
| STIMuSTEP [ | FSRs | Implanted | 2 | Dorsiflexion, eversion | Peroneal nerve |
| ActiGait [ | FSRs | Implanted | 4 | Dorsiflexion and plantarflexion | Peroneal nerve, tibial and peroneal muscles |
| FESIA WALK [ | IMUs | Transcutaneous | Multi-pad | Dorsiflexion | Tibialis anterior and peroneal nerve |
| WalkAide [ | Tilt sensor | Transcutaneous | 1 | Dorsiflexion | Tibialis anterior and peroneal nerve |
a Note: the system is reported to be modular and can scale up the number of sensors
Fig. 4Classification of FD neuroprostheses included in this review. Type of sensors, control approach, number of available stimulation channels, type of electrodes and application type are summarized with references in brackets inside the descriptive knobs
Take-Home Messages
| Key issues | Recommendations |
|---|---|
| The adequate wave profile for a more effective stimulation is not clear | Studies on muscle synergies in healthy people can help determine these stimulation profiles, as well as the most appropriate muscle activations based on these wave profiles to achieve a movement as close to physiologically healthy |
| Implanted vs transcutaneous electrodes | The development of transcutaneous stimulation systems that use electrode arrays to achieve an adequate stimulation by means of an auto setup with virtual electrodes can promote and facilitate their unsupervised use, favoring the use of these systems compared to those that apply implanted electrodes |
| Daily FD neuroprosthesis use is crucial | The daily use is beneficial and the design and development of portable multichannel neuroprosthesis with auto setup seeks to increase it, as well as improve the assistance provided |
| Musculature stimulation strategy | The muscle stimulation of FD is mainly based on the assistance of the anterior tibial or peroneal nerve during the swing phase. However, the results of different studies suggest that the assistance of the plantar flexors is also of great importance in solving this pathology |
| Best sensors or sensors combination | The combination of FSRs and IMUs has been the most optimal solution in terms of gait event detection. Nevertheless, advances in gait event detection through an EEG or EMG can help in many cases to perform an adequate gait phase detection and in parallel control muscle fatigue |
| A reduction of muscle fatigue does not have a clear solution | The combination of CFT and VFT, the selection of an appropriate stimulation wave profile and the use of closed-loop control systems may have the potential to generate physiological movements by reducing the fatigue produced |
| Open-loop vs Closed-loop | Open-loop systems are very popular owing to their easy implementation, but do not solve muscle fatigue, nonlinear problems, or the variable response over time. Closed-loop control systems can be a solution. Currently, the most popular method is the ILC, because this control technique is able to provide such adaptability and applies automatic learning in a simple way; however, the systems based on an EMG and ENG present a potentially useful option if the processing difficulties, which are generated with artifacts introduced through the assistance, are solved |
| Closed-loop control systems still do not cross the trade barrier | Although they are a very promising solution, a suitable strategy for solving problems such as fatigue, non-linear muscle response and time variable has not yet been found. |
| Unilateral assistance is widespread | Regardless of the affected side, the design and development of FD neuroprosthetics and strategies that allow bilateral assistance can introduce significant advances in the search for optimal therapies for the treatment of FD |
| Most of the studies have focused on a biomechanical analysis, specifically kinematics | With novel advances, the combined use of biomechanical and EMG analyses can be useful to improve the understanding of the movement and the effects produced by the assistance |
| Systems are tested in ideal scenarios that are far removed from reality | In everyday life we find inclined planes, stairs and other obstacles, not just horizontal flat surfaces to walk on. |
| There is a lack of evidence of long-term therapeutic results | Most of the studies have focused on the instantaneous effect of the assistance or the effect in the short-term, and it is necessary to observe the implications of the use of a long-term neuroprosthesis for the design of personalized therapies that adapt to the evolution of the pathology |
| Non-progressive vs progressive diseases treatment | A different approach seems to be necessary when treating FD in non-progressive and progressive diseases. In this sense, the use of implanted systems in individuals with progressive pathologies plays an important role, although the development of systems with arrays of electrodes can be very relevant and replace them. |