INTRODUCTION
Parkinson's disease (PD) is a progressive neurodegenerative disorder affecting millions
of individuals worldwide, significantly burdening patients and their caregivers.[1] Among the myriad of symptoms associated with PD, gait disturbances are one of the
most prevalent and debilitating, contributing to a substantial decline in the quality
of life (QoL).[2] Although many resources are available for the management of PD motor symptoms, gait
impairment only partially benefits from antiparkinsonian drug treatment and surgical
intervention.[1]
[3]
Assistive Technology (AT) is an umbrella term covering the systems and services related
to the delivery of assistive products (AP) and services, enabling, and promoting the
inclusion and participation of persons with disability, aging populations, and people
with non-communicable diseases. Therefore, the use of AP may maintain or improve PD
patients' functioning and independence, thereby promoting their well-being (WHO assistive
- https://www.who.int/health-topics/assistive-technology#tab=tab_1). AT may be an asset in the rehabilitation program[4] and development of devices enabling objective, accurate, and better gait assessment
and monitoring is crucial for people with PD.[5]
In response to this pressing need, novel rehabilitation interventions and technology
have emerged, offering new avenues for assisting individuals with PD in managing their
gait difficulties.[6]
[7] The search for innovative interventions has led to the surge of numerous gait AP
such as wearable devices,[8] robotic exoskeletons,[9]
[10] Robot-assisted and treadmill,[11] virtual reality (VR),[12]
[13] exergames-based interventions,[14] smartphone or mobile health applications,[15] and sensor-based systems[16] among others. These AP, with diverse mechanisms of action, provide real-time feedback
on gait parameters, promote targeted rehabilitative exercises, and may enhance overall
gait performance.[5]
[15]
A better understanding of emerging AT to assess gait in PD is important since it continues
to advance and become more available. However, keeping pace with rapidly evolving
technologies is challenging. Recognizing the potential and utility of these AP for
assessing or improving mobility will help consumers and researchers to better manage
and broaden their applicability in rehabilitation or clinical practice.
Herein, this review aims to provide an overview of current AT interventions for PD
gait rehabilitation. We hope to enable healthcare professionals to understand the
available technologies and their clinical and rehabilitation applications. For this
purpose, we compiled and synthesized the existing body of literature and selected
studies that assessed the efficacy, usability, and acceptability of current technological
interventions. We also explored the outcomes of recently published studies, including
improvements in gait speed, balance, stride length, and fall risk of PD patients.
RESULTS
We only included studies that met all inclusion criteria after analyzing their respective
titles, abstracts, and texts. In total, we selected 412 studies. We included 72 studies
that met all inclusion criteria. Several types of technological devices used to evaluate
and treat gait in Parkinson's disease were identified.
We found several assistive technology devices for gait analysis, and they are used
to identify and diagnose gait and other motor symptoms (EEG, EMG, Azure Kinect, HTC
VIVE VR; GAITRite Portable Walkway System),[18]
[19]
[20]
[21] to track gait and motor symptoms (VIBE),[22]
[23] and to treat gait (Keeogo Reha exoskeleton, Tymo system; Treadmills, Gait Trainer
GT1, Lokomat, Cycle Ergometers, Walkbot-S, Non-motorized treadmill, G-EO system, SMART
Lounge vibroacoustic system, Smart shoes, XaviX system, App “PatientConcept”).[18]
[24]
[25]
[26]
[27]
[28]
[29]
The most frequently used systems in gait analysis are motion capture systems (3D systems,
multi-sensors combined or optoelectronic systems, 3D systems, multi-sensors combined
or optoelectronic systems),[20]
[21] inertial Measurement Unit (IMU)[20]
[30]; and force plates.[20] Other studies monitoring gait parameters in PD used wearable sensors or wearable
devices based on different types of sensors.[31]
[32]
[33]
[34]
[35]
[36]
[37]
[38]
[39]
Two guideline reviews emphasized the high level of evidence of cueing techniques using
real feedback to improve gait performance.[3]
[6] We also found some studies using devices as compensation strategies to improve gait
in PD such as visual laser cues,[40] rhythmical auditory cues provided by a metronome,[41] and tactile cues.[42]
Some studies used VR to interact three-dimensional virtual environment.[4]
[25]
[43]
[44]
[45]
[46]
[47]
[48]
[49]
[50]
[51]
[52]
[53]
[54]
[55]
[56]
[57]
[58]
We also found studies using Robotic-assisted gait training for PD.[24]
[29]
[59]
[60]
[61]
[62]
We analyzed several types of AP and categorized them into commercial and non-commercial
devices available for research, rehabilitation, or home-based care. The majority of
them are available on the market and depicted in [Table 1]. To make for easy reading, and based on the interventions that were described, we
subdivided our findings into the following subtopics: wearable sensors, gait analysis,
real-time feedback and cueing techniques, VR, and robotics.
Table 1
Overview of tradeable and non-tradeable devices
|
Type of assistive products
|
Devices
|
Manufacturers of commercial and non-commercial devices available
|
|
Apps
|
PatientConcept
|
NeuroSys GmbH
|
|
ListenMee APP
|
Human Bionics SAS
|
|
Net MD system
|
Smartwatch3 SWR50 model, Sony
|
|
Gait and balance systems
|
3-D Motion Capture systems
|
ActiGraph LEAP™
|
|
EquiTest Computerized Dynamic Posturography unit
|
NeuroCom International Inc.
|
|
Force Plate
|
NI
|
|
Force Sensitive Resistor (FSR)
|
NI
|
|
GAITRite Portable Walkway System
|
CIR Systems Inc.
|
|
Inertial Measurement Unit (IMU)
|
Heel2Toe TM
Shimmer Research Ltd.
|
|
Multi-sensors combined
|
CuPiD System Project
|
|
Optoelectronic systems
|
NI
|
|
Smart-EquiTest Balance Master system
|
NeuroCom International Inc.
|
|
Tymo system
|
Tyromotion Inc.
|
|
VICON motion capture system
|
Vicon Motion SystemsLtd
|
|
Mobile Motion Visualizer
|
System Friend
|
|
Exoskeletons
|
Walkbot-S
|
P&S Mechanics
|
|
Keeogo Rehab exoskeleton
|
B-Temia Inc
|
|
Stride Management Assist exoskeleton
|
Honda R&D Co., Ltd
|
|
Yorisoi robot
|
Sanyo Homes
|
|
Robot-assisted walking
|
G-EO system
|
Reha Technology AG
|
|
Gait Trainer GT1
|
RehaStim Medtec AG
|
|
Lokomat
|
Hocoma
|
|
Virtual reality equipments
|
Microsoft Kinect and Xbox gaming console
|
Microsoft Inc.
|
|
HTC VIVE VR
|
HTC and Valve Corporation
|
|
Nitendo wii
|
Nintendo Co., Ltd.
|
|
Tymo
|
Tyromotion Inc.
|
|
MOTIGRAVITY system
|
NI
|
|
V-TIME Project equipamento
|
NI
|
|
Smart shoes
|
JiBuEn gait analysis
|
|
Insole sensors
|
Insole
|
BalancePRO
|
|
Smart insole + app
|
Walk With Path Ltd.
|
|
Moticon sensor insole
|
Moticon ReGo AG
|
|
Others
|
Electroencephalography (EEG)
|
NI
|
|
Electromyography (EMG)
|
NI
|
|
Google Glass
|
Google Inc.
|
|
Non-motorized treadmill
|
NI
|
|
Recumbent Cycle Ergometers
|
NI
|
|
SMART Lounge vibroacoustic system
|
NI
|
|
Smart shoes
|
NI
|
|
Smartphone
|
NI
|
|
Treadmills
|
NI
|
Abbreviation: NI, not informed.
DISCUSSION
Wearable sensors
The advancement of sensor technology, motion capture systems, and force platforms
have been employed as more objective and precise methods for evaluating PD patient's
gait.[33] Sensor and Wearable devices (SWD) facilitate and monitor an individual's activity.
They are an important asset for intervention and monitoring and are easy to integrate
into the patients' daily routines.[31] SWD enables the remote assessment of patients' conditions in their natural environment,
promoting a more comprehensive clinical evaluation and empowering patients to monitor
their gait.
Most of the SWD sensors to analyze spatio-temporal parameters of gait in patients
with PD were placed on both ankles and tibias, feet, chest, and lower back. For gait
parameters, speed was the most common feature evaluated, followed by cadence, stride
length, and stride time. For step characteristics, step time, step length, and right-left
asymmetry were mostly assessed.[32]
Many low-cost devices have been employed to collect real-time spatiotemporal, kinematic,
and kinetic gait features in PD patients. Costly force platforms used to measure ground
reaction force during gait may be replaced by pressure insole. These insoles are composed
of an accelerometer, gyroscope, and sometimes a magnetometer attached to the patient
and can measure the linear and angular velocity, acceleration, and other gait parameters.[35] Sensors may also be placed under smart shoes and inertial microelectromechanical
system sensors attached to the patients to measure stride length, gait velocity, range
of motion of the ankle, knee, and hip joints of individuals with PD.[36] Other studies are focusing on developing new SWD to detect the occurrence of freezing
of gait (FOG) and its discrimination in PD (freezing, shuffling, and trembling),[37] and promising resources may be launched in the near future.[38]
These AP have also been tested to discriminate PD individuals from healthy controls.
A recent study explored which parameter could discriminate PD from controls, and they
observed that kinematic features were more informative than kinetic analysis.[39] Smartphones are a promising tool to discriminate gait and postural instability between
healthy controls and individuals with PD.[63] However, it has also been used to promote home-based gait training, so future research
should investigate the role of smartphones as an AP for home-based rehabilitation
support.
Moving arms in a rhythmic and symmetrical contributes to postural stability and walking
efficiency. SWD may also be placed on the upper limb and are useful to measure the
arms arm swing during walking. One trial used a motion-capture system computer with
speech models and advanced artificial intelligence sensors for orientation and spatial
tracking to collect 3-dimension joint trajectories and body segments during walking.
The authors could quantify arm swing features as well as lower gait velocity of PD
patients compared to healthy controls, thus offering a simple tool to provide a more
comprehensive gait assessment.[64]
[65]
A recent consumer-centered review described the available commercial SWD targeting
improvement in gait patterns and walking behavior. Of the 11 commercially available
devices, only 4 (36%) had findable evidence for efficacy potential supporting the
claims.[34] Although there are promising results with SWD for gait assessment, many challenges
need to be overcome. To cite some, gait requires complex algorithms for its analysis,
and most of the available portable devices do not avoid noise contamination or provide
precise data synchronization and collection of real-time spatiotemporal, kinematic,
and kinetic parameters. Available SWD capture short walking bouts and good gait quality
measures cannot rely on short interval data. Moreover, gait assessment obtained from
laboratory machine learning methods does not necessarily reflect gait features in
patients' daily living. New algorithms and sensor detectors resolution improvements
are needed to accurately extract facets of gait quality and function.[64] Future devices should be sensitive to precisely distinguish between healthy controls
and early or mild symptomatic PD patients and also provide accurate gait parameters
enabling early intervention of patients with a higher risk for falling or FOG.
Gait analysis
Emerging technology for gait analysis aims to identify and diagnose abnormal gait
parameters in PD, but it may also be used to monitor and improve gait, balance, and
mobility.[7] Currently, most of the devices used for gait analysis can be categorized into a)
motion capture systems (3D systems, multi-sensors combined or optoelectronic systems);
b) inertial measurement unit; and c) force plates.[20]
[22]
[30]
[66]
Most of the trials for gait analysis evaluated its speed with good reliability. The
Berg Balance Scale and UPDRS part III were often used for outcome ratings. Overall,
the AP were well accepted by the patients.[10]
[18]
[22]
[23]
[24]
[25]
[26]
[27] Other parameters frequently assessed in the studies besides gait speed were: step
length, step symmetry, falls and freezing of gait.[28]
[29]
[30]
[66] Assistive devices obtained significant correlations on PD gait analysis in at least
one of the above-mentioned parameters. However, the effectiveness of these AP and
the outcomes are variables since they cannot yet overcome laboratory gait conventional
monitoring or replace validated PD gait assessment tests or scales. Still, some commercial
devices have been efficacious for the analysis and treatment of gait and balance in
PD.[10]
[18]
[20]
[27]
Many AP devices not only assess but are also ancillary for gait and balance rehabilitation
treatment. In this aspect, gait assistance robots (GAR), such as the G-EO system,
Gait Trainer GT1, Lokomat, and GAITRite are the preferred equipment for this purpose.[10]
[18]
[27]
[29] Another gait treatment strategy is to combine traditional treadmill training with
assessment assistive devices.[18] Before long, more walking aid gadgets and innovative AP will be launched on the
market combining both evaluation and treatment strategies[28] and more trials will be necessary to explore their plausibility and effectiveness
in clinical practice.
Despite the promising potential of assisted technology for gait analysis, several
challenges and questions remain unaddressed.[67] Several barriers may be listed for its limited utilization as a gait rehabilitation
tool such as high cost, unfamiliarity with technology, technical issues, low usability,
and so on. Being so, strategies to increase awareness and make this resource generally
available are welcome and may help to broaden assistive devices accessibility for
research, clinical, and consumers use. As an example, in the last years, there has
been an increasing process for portability and miniaturization of mobile health technologies.[7]
Furthermore, ethical concerns regarding data privacy, patient autonomy, and equitable
access to technology must be examined in-depth. Additionally, the use of these devices
and outcomes on the role of telehealth and remote monitoring in delivering personalized
gait analysis programs requires further exploration, especially in the context of
evolving healthcare practices and digital health solutions. So, due to the complexity
of PD gait management, perhaps advances in artificial intelligence may, in near future,
promote, refine analyses, and support treatment strategies in PD gait rehabilitation.
Real-time feedback and cueing techniques (auditory, visual, and proprioceptive)
The positive effects of the cues on gait performance (speed, cadence, step length,
and stride) are well recognized and supported by a robust level of evidence.[3]
[6] External cues, such as auditory and visual ones, are used to bypass and compensate
for the brain's abnormal internal cueing mechanisms that cause deficiencies in movement
planning and execution in PD.[2]
These compensation strategies (or cueing techniques) delivered by physiotherapists,
such as multimodal training, may provide feedback, repetition, and high challenges
and can be used to correct temporal aspects of gait, improve balance and walking speed
and prevent freezing episodes.[41] It has been demonstrated that people with PD training with audio cues, such as a
digital metronome improve balance and gait performance.[41] Besides, cueing training may overcome or ameliorate FOG episodes in the short and
long term.[68] Moreover, cueing may be applied to different mobile health applications,[15] and digital devices such as robot-assisted rhythmic cues[59] or laser attached to patient's shoes (the laser shoes).[40]
Additionally, proprioceptive devices, such as tactile cues or vibratory ones, are
being explored to provide external support during walking.[42] Finally, visual, and auditory cues can be combined with treadmill training, and
it has shown to be better than standard treadmill training alone.[46] This association may focus on gait and cognitive deficits to optimally address several
critical aspects of fall risk and improve mobility, physical activity, cognitive function,
and FOG in PD.
Virtual reality
VR is a computer technology that enables users to interact in a three-dimensional
(3D) virtual environment and experience similar situations in the real world. This
technology facilitates the perception of physical movements and visual, auditory,
and tactile input. VR can be categorized into three types according to the degree
of immersion: non-immersive,[4] semi-immersive,[52] and full-immersive.[63] In a non-immersive system, the patient can interact with the virtual environment
using a computer screen and game console.[4] A semi-immersive VR system consists of large screens or projections to enable a
visual-virtual 3D-space experience and uses interactive devices such as a motion tracker,
haptic gloves, and balance platform.[52] Fully immersive VR incorporates the combination of more sophisticated graphic systems
to create a virtual world and advanced wearable devices. It allows users to safely
and effectively experience motor challenging situations at their own pace and difficulty
level and can observe their performance in real-time, receiving immediate feedback
regarding movement and balance control.[69]
Exergame is the gamification of rehabilitation using electronic games that capture
and simulate real movements. It requires the participants to be physically active
or exercise and apply full body motion to play the games.[70] It is a low-cost and accessible approach for healthcare professionals to incorporate
this training in rehabilitation programs. Examples of exergames resources are Nintendo
Wii, Kinect, and games designed for computers or sensors like Leap Motion.[70] Therapy based on commercial video games increases patients' motivation, provides
direct feedback, and allows dual-task training.[49] This exercise modality appears to benefit functional circuitry in PD and facilitates
learning through reinforcement feedback.[69] The training approach promotes sensory input, central integration, coordination,
weight transfer, and balance, with subsequent improvements in muscle control and coordination,
and might improve motor function in neurological disorders.[53]
Studies have shown that short-term exergame associated or not with conventional training
may improve QoL,[43] postural instability, balance,[44]
[54] mobility, gait parameters, and reduced risk of falls in PD.[25] These findings were endorsed by a systematic review in which exergame training reduced
the number of falls and improved static and dynamic balance in patients with PD.[4] It is worth highlighting that in order to improve balance, a supervised VR program
might require at least 20 minutes, 4 to 6 times a week of training[54] and that younger patients have better outcomes than older ones.[55] The longer-term efficacy of VR and exergames interventions is still unclear, therefore,
more trials are needed to address these questions.
Immersive VR with body weight supported treadmill warrants PD patients to exercise
in a safer condition. It provides repetitive, task-oriented, and higher-intensity
training. The association of both apparatuses with a 20% body weight support improves
gait and balance assessment.[58] Moreover, those who trained with the treadmill and VR had fewer falls than those
with the treadmill only, but no changes were found for FOG.[45] The benefit may vary according to training duration, PD patients who underwent a
12-week exercise program had better gait speed, stride length under dual-task conditions,
and falls reduction compared to a 6-week VR training.[46]
So far, most of the studies evidenced that VR rehabilitation may have beneficial effects
on balance. In relation to gait, improvements in speed, step length, and cadence in
both kinematics and clinical scale tests were observed,[49] but no significant differences were seen in walking speed in PD.[56] On the other hand, a meta-analysis showed no statistically significant differences
in gait ability, activity of daily living, motor function, and QoL in PD after VR
training.[57] It is noteworthy that a meta-regression analysis utilizing publication year as the
predictor variable showed a greater improvement in balance function in recent studies
compared with older ones. This could be attributed to the technological advancement.
VR has become cheaper and more accessible, enabling more patient enrollment in trials
and resulting in greater data accessibility.
Studies observed that VR rehabilitation may improve neuroplasticity and change brain
neural patterns by activation and reorganization mainly of the primary motor cortex,
sensorimotor cortex, and supplementary motor area.[48] In addition, functional magnetic resonance imaging showed that PD patients who underwent
VR training increased activity in the precuneus region, which is linked to visuospatial
integration, memory, and self-awareness, and this network is active during activities
involving memory encoding and retrieval.[47] Cognition plays an important role in postural control and may interfere with gait
and posture assessment and treatment.[71] So, advances in artificial intelligence (AI) may promote and refine strategies for
VR in PD rehabilitation. It will allow more precise interventions since gait is very
complex and an excessive number of features requires robust computing power to obtain
more accurate gait performance analysis.[72] This analysis could help detect the onset of walking abnormalities, revealing the
transition from normal to pathological gait.
Besides AI will offer better resolutions of patients' data, and identify parameter
changes and PD symptoms and severity, which may be shared across healthcare networks
and members of the interdisciplinary team, offering more personalized treatment.[15] PD rehabilitation could benefit in near future from a more effective approach with
more challenged and realistic virtual environment.[52] Finally, VR rehabilitation should be offered to PD patients as a supplementary approach
to existing proven and safe interventions until further and more robust evidence is
available.[50]
[51]
[53]
[57] Hence, large trials with good methodologic designs are necessary with a focus on
comparing the efficacy of VR-based rehabilitation with conventional treatments and
or new emerging technologies.
Robotics
Robotic-assisted gait training (RAGT) has been employed for PD patients as a complementary
approach to conventional rehabilitation treatment.[61] These AP devices support the body weight, control body sway and improve the safety
profile, which may benefit balance, postural control, and gait parameters.[10] Repetitive locomotor training may also facilitate neuromuscular regulation, provide
proprioceptive cueing effect, shift the body weight from one leg to the other, reduce
muscle co-contraction, improve contraction/inhibition patterns, and strengthen lower
limbs. The gait-like movement may also have a positive effect on the gait central
pattern generators at the spinal level.[27]
[29]
There are a variety of robots utilized for rehabilitation including exoskeletal robots
equipped with treadmills and end-effector robots. Robotic treadmills, such as the
Lokomat gait training system, improve gait performance,[27] and can also be associated with VR to increase cognitive flexibility and attention
shifting, as well as in executive and visuospatial skills. Visual cueing, displaying
incentive messages on a screen, and auditor feedback when training with RAGT, are
resources to improve the rhythm of the gait of individuals with PD.[59] An automated wearable exoskeleton robot may detect the hip joint angle and provide
torque to assist in hip flexion and extension facilitating gait training.[60]
Some studies have shown the beneficial effects of RAGT for FOG in PD. One study compared
treadmill gait training with RAGT. PD patients had improvement in all the outcome
measures (6-minute walk test, TUG, FOG, and QoL), but freezers experienced a better
reduction in FOG with RAGT than control group training with treadmill alone.[29] The hypothesis mechanism suggests that repetitions of rhythmic limb movements could
act as an external proprioceptive cue, by reinforcing the neuronal circuits that contribute
to the lower limb movements. Another possibility is that proprioceptive cues might
be the same as visual and auditory cues, so they might be involved in improving gait
patterns.[61] Fall may also be prevented by body weightlifting wearable snuggling nursing robot.
It has been shown that such a device may aid PD patients' gait performance during
TUG test and offer a good level of security in preventing falls.[62]
There is growing evidence suggesting that the utilization of these computerized technologies
could potentially transform conventional therapies by facilitating safety and real-time
assessments of PD patients.[73] This finding was confirmed by a meta-analysis study, however, RAGT does not impact
on the gait velocity or walking distance of patients with PD.[74] RAGT may also benefit PD patients' gait endurance.[24] Therefore, assistant robotic device training can improve gait parameters with reduced
motor workload in PD patients,[34] but more studies should be done to confirm these findings.
Summary of evidence
This review aimed to identify and synthesize key trends in AT. New technologies may
be used for assistance, diagnosis, monitoring, prediction of treatment response, and
assistance with therapy or rehabilitation in PD patients' gait. Although many AP resources
are available, only few are actually implemented in daily clinical practice. We found
some hindrances to the limited use of AT and awareness of these factors may lessen
the barriers between the fast-developing technological devices and consumers, making
them more accessible and also broadening their implementation in PD patients' daily
living or treatment.
Besides technological issues, a lack of motivation to use WSD monitoring systems is
an aspect someone also must be observant of. Patients' empowerment, gaining knowledge
about new AT devices, and their participation as active players in the development
of research activities may also favorably increase their adherence. In addition, usability
and familiarity with new devices contribute to high satisfaction of using technology
in people with PD. Tailoring the best device for each individual, greater patients'
gait characterization, more patient engagement and self-assessment are details to
be always reminded of when selecting AP for patients' rehabilitation.
Finally, research is needed to explore the real role of AP in PD. We also need to
better ascertain which technology resource will be more appropriate for gait assessment
in PD. We hope his review may inspire further research, foster innovation, and to
help readers to prescribe more effective and personalized technological interventions
for individuals living with PD.
Key points
-
Although AT is a valuable tool for PD management, it is not widely implemented in
daily clinical practice.
-
Understanding of emerging technology is important and facilitates the recognition
of the potential and utility of new AP for assessing and improving gait in PD.
-
Patient empowerment and their inclusion as active players in the development of research
activities may favorably impact compliance.
-
Enjoyable, cheaper, safer, easier to use, and friendly devices may contribute to adherence
to using technology.
Limitations
Limitations for this review include missed original literature on technology and gait
assessment, despite our best efforts to search for relevant articles and sources derived
from our references. We hoped to provide a scope description of all original research
on AT and gait however, we did not conduct a formal quality assessment of included
studies and our findings could be influenced by publication bias.
In conclusion, this review provided a comprehensive synthesis of the current evidence
and limitations of assisted technology in managing PD gait impairments. Assisted Technology
in PD gait aspires to be a valuable resource for advancing our understanding of how
technology can improve the lives of PD patients since this is a rapidly evolving field
with an increasing number of publications in recent years. With the understanding
of the potential of such devices and the existing research landscape, we hope to guide
future investigations and inspire further research, innovation, and the development
of more effective and personalized interventions for individuals living with PD.
