A Trunk Support System to Identify Posture Control Mechanisms in Populations Lacking Independent Sitting

Quantifying States and Transitions of Emerging Postural Control for Children Not Yet Able to Sit Independently

Objective, quantitative postural data is limited for individuals who are non-ambulatory, especially for those who have not yet developed trunk control for sitting. There are no gold standard measurements to monitor the emergence of upright trunk control. Quantification of intermediate levels of postural control is critically needed to improve research and intervention for these individuals. Accelerometers and video were used to record postural alignment and stability for eight children with severe cerebral palsy aged 2 to 13 years, under two conditions, seated on a bench with only pelvic support and with additional thoracic support. This study developed an algorithm to classify vertical alignment and states of upright control; Stable, Wobble, Collapse, Rise and Fall from accelerometer data. Next, a Markov chain model was created to calculate a normative score for postural state and transition for each participant with each level of support. This tool allowed quantification of behaviors previously not captured in adult-based postural sway measures. Histogram and video recordings were used to confirm the output of the algorithm. Together, this tool revealed that providing external support allowed all participants: (1) to increase their time spent in the Stable state, and (2) to reduce the frequency of transitions between states. Furthermore, all participants except one showed improved state and transition scores when given external support.

Nonlinear Response of Human Trunk Musculature Explains Neuromuscular Stabilization Mechanisms in Sitting Posture

OBJECTIVE

Determining the roles of underlying mechanisms involved in stabilizing the human trunk during sitting is a fundamental challenge in human motor control. However, distinguishing their roles requires understanding their complex interrelations and describing them with physiologically meaningful neuromechanical parameters. The literature has shown that such mechanistic understanding contributes to diagnosing and improving impaired balance as well as developing assistive technologies for restoring trunk stability. This study aimed to provide a comprehensive characterization of the underlying neuromuscular stabilization mechanisms involved in human sitting.

APPROACH

This study characterized passive and active stabilization mechanisms involved in seated stability by identifying a nonlinear neuromechanical physiologically-meaningful model in ten able-bodied individuals during perturbed sitting via an adaptive unscented Kalman filter to account for the nonlinear time-varying process and measurement noises.

MAIN RESULTS

We observed that the passive mechanism provided instant resistance against gravitational disturbances, whereas the active mechanism provided delayed complementary phasic response against external disturbances by activating appropriate trunk muscles while showing non-isometric behavior. The model predicted the trunk sway behavior during perturbed sitting with high accuracy and correlation (average: 0.0007 [rad2] and 86.77%). This allows a better mechanistic understanding of the roles of passive and active stabilization mechanisms involved in sitting.

SIGNIFICANCE

Our characterization approach accounts for the inherently nonlinear behavior of the neuromuscular mechanisms and physiological uncertainties, while allowing for real-time tracking and correction of parameters' variations due to external disturbances and muscle fatigue. The outcome of our research, for the first time, (1) allows a better mechanistic understanding of the roles of passive and active stabilization mechanisms involved in sitting; (2) enables objective evaluation and targeted rehabilitative interventions for impaired balance; facilitate bio-inspired designs of assistive technologies, and (3) opens new horizons in mathematical identification of neuromechanical mechanisms employed in the stable control of human body postures and motions.

Study on the Effects of Different Seat and Leg Support Conditions of a Trunk Rehabilitation Robot

Performance of trunk rehabilitation exercises while sitting on movable surfaces with feet on the ground can increase trunk and leg muscle activations, and constraining the feet to move with the seat isolates control of the trunk. However, there are no detailed studies on the effects of these different leg supports on the trunk and leg muscle activations under unstable and forcefully perturbed seating conditions. We have recently devised a trunk rehabilitation robot that can generate unstable and forcefully perturbed sitting surfaces, and can be used with ground-mounted or seat-connected footrests. In this study, we have evaluated the differences in balance performance, trunk movement and muscle activation (trunk and legs) of fourteen healthy adults caused by the use of these different footrest configurations under the different seating scenarios. The center of pressure and trunk movement results show that the seat-connected footrest may be a more suitable choice for use in a balance recovery focused rehabilitation protocol, while the ground-mounted footrest may be a more suitable choice for a trunk movement focused rehabilitation protocol. Although it is difficult to make a clear selection between footrests due to the mixed trends observed in the muscle activation results, it appears that the seat-connected footrest may be preferable for use with the unstable seat as it causes greater muscle activations. Furthermore, the results provide limited evidence that targeting of a particular muscle group may be possible through careful selection of the seat and footrest conditions. Therefore, it may be possible to utilize the trunk rehabilitation robot to maximize the training outcomes for a wide range of patients through careful selection of training protocols.

Postural mechanisms in moderate-to-severe cerebral palsy

People with moderate-to-severe cerebral palsy (CP) have the greatest need for postural control research yet are usually excluded from research due to deficits in sitting ability. We use a support system that allows us to quantify and model postural mechanisms in nonambulatory children with CP. A continuous external bench tilt stimulus was used to evoke trunk postural responses in seven sitting children with CP (ages 2.5 to 13 yr) in several test sessions. Eight healthy adults were also included. Postural sway was analyzed with root mean square (RMS) sway and RMS sway velocity, along with frequency response functions (FRF, gain and phase) and coherence functions across two different stimulus amplitudes. A feedback model (including sensorimotor noise, passive, reflexive, and sensory integration mechanisms) was developed to hypothesize how postural control mechanisms are organized and function. Experimental results showed large RMS sway, FRF gains, and variability compared with adults. Modeling suggested that many subjects with CP adopted "simple" control with major contributions from a passive and reflexive mechanism and only a small contribution from active sensory integration. In contrast, mature trunk postural control includes major contributions from sensory integration and sensory reweighting. Relative to their body size, subjects with CP showed significantly lower damping, three to five times larger corrective torque, and much higher sensorimotor noise compared with the healthy mature system. Results are the first characterization of trunk postural responses and the first attempt at system identification in moderate-to-severe CP, an important step toward developing and evaluating more targeted interventions.NEW & NOTEWORTHY Cerebral palsy (CP) is the most common cause of motor disability in children. People with moderate-to-severe CP are typically nonambulatory and have major impairments in trunk postural control. We present the first systems identification study to investigate postural responses to external stimulus in this population and hypothesize at how the atypical postural control system functions with use of a feedback model. People with moderate-to-severe CP may use a simple control system with significant sensorimotor noise.

3D posture visualisation from body shape measurements using physics simulation, to ascertain the orientation of the pelvis and femurs in a seated position

BACKGROUND AND OBJECTIVE

The paper presents a novel technique for the visualisation and measurement of anthropometric features from patients with severe musculoskeletal conditions. During a routine postural assessment, healthcare professionals use anthropometric measurements to infer internal musculoskeletal configuration and inform the prescription of Custom Contoured Seating systems tailored to individual needs. Current assessment procedures are not only time consuming but also do not readily facilitate the communication of musculoskeletal configuration between healthcare professionals nor the quantitative comparison of changes over time. There are many techniques measuring musculoskeletal configurations such as MRI, CT or X-ray. However, most are very resource intensive and do not readily lend themselves to widespread use in, for example, community based services. Due to the low volume of patient data and hence small datasets modern machine learning techniques are also not feasible and a bespoke solution is required.

METHODS

The technique outlined in this paper uses physics simulation to visualise the orientation of the pelvis and femurs when seated in a custom contoured cushion. The input to the algorithm is a body shape measurement and the output is a visualised pelvis and femurs. The algorithm was tested by also outputting a multi-label classification of posture (specific to the pelvis and femurs).

RESULTS

The physics simulation has a classification accuracy of 72.9% when labelling all 9 features of the model; when considering 6 features (excluding rotations about the x-axis) the accuracy is increased to 92.8%.

CONCLUSIONS

This study has shown that a mechanical shape sensor can be used to capture the unsupported seated posture of an individual during a clinic. The results have demonstrated the potential of the physics simulation to be used for anthropometric feature extraction from body shape measurements leading to a better posture visualization. Capturing and visualising the seated posture in this way should enable clinicians to more easily compare the effects of clinical interventions over time and document postural changes. Overall, the algorithm performed well, however, in order to fully evaluate its clinical benefit, it needs to be tested in the future using data from patients with severe musculoskeletal conditions and complex body shapes.

Influence of visual biofeedback and inherent stability on trunk postural control

BACKGROUND

For individuals who never achieve independent standing, rehabilitation is focused on trunk posture and balance control. Visual biofeedback has the potential to augment sitting balance training, however previous work in this area has been limited to standing.

RESEARCH QUESTION

To what extent do different types of visual biofeedback influence trunk sway in sitting?

METHODS

Twelve healthy young adults sat on an articulating bench. During 'sway referencing' trials, the bench tilted up and down in proportion to trunk sway in the frontal plane. This paradigm increased difficulty of the balance task and required participants to rely on visual and vestibular cues. Participants were provided different visual biofeedback through a rotating needle-gage display. Trials lasted 165 s, were ordered randomly, and included either direct feedback (needle rotated in proportion to body sway), inverted feedback (needle rotated in the opposite direction of sway), time delayed feedback (0.5 s), random feedback, eyes closed, or control (eyes open with screen off). To explore the impact of inherent stability, trials were repeated with and without external trunk support.

RESULTS

Body sway depended on feedback type. Specifically, direct and inverted feedback reduced root-mean-squared (RMS) sway the most, time delayed feedback had a smaller effect, and random visual feedback increased participants' RMS sway compared to control. Frequency domain analyses demonstrated direct and inverted visual feedback reduced sway amplitude at the lower frequencies while having minimal effect on (or increasing) sway amplitude at higher frequencies.

SIGNIFICANCE

This study extends previous work by showing that visual biofeedback can have powerful effects on sitting balance, even with external support. Results from the different types of feedback conditions further our understanding of how the brain interprets visual biofeedback. Frequency-based results were similar to previous studies using different modalities and suggest participants interpret biofeedback through sensory addition as opposed to sensory substitution.

Specificity and variability of trunk kinematics on a mechanical horse

As perturbation training is gaining popularity, it is important to better understand postural control during complex three-dimensional stimuli. One clinically relevant and commonly used three-dimensional stimulus is found in hippotherapy and simulated hippotherapy on a mechanical horse. We tested nine healthy participants on a horse simulator, measured head and trunk kinematics, and characterized data in time (root-mean-square and variability) and frequency (amplitude spectra, gains, and phases) domains. We addressed three fundamental questions: 1) What is the specificity of postural responses to the simulator? 2) Which plane of motion is associated with the most and least variability (repeatable movements across repeated stimuli and across participants)? 3) To what extent are postural responses influenced by different degrees of stability (addition of pelvis straps and trunk support)? We found head and trunk responses were highly specific to the three-dimensional simulator perturbation direction and frequency. Frontal plane responses had the least variability across repetitions and participants whereas transverse motion was most variable. Head motion was more variable than the trunk at low frequencies and exhibited a marked decrease in tilt in the sagittal plane. Finally, the inclusion of pelvis straps had minimal effect on kinematics at low frequencies but altered higher frequencies; whereas added trunk support reduced head and trunk responses to perturbations and altered timing characteristics in all three planes. In conclusion, the present study suggests that frontal plane motion was under a high level of control, and results support the idea that specific head and trunk postural responses can be elicited from a complex three-dimensional stimuli, such as those found in hippotherapy. Researchers and clinicians can use results from this study to help interpret variability, implement mechanical adjustments to stability, and assess responses in pathological populations.

Sensorimotor control of the trunk in sitting sway referencing

We developed a sway-referenced system for sitting to highlight the role of vestibular and visual contributions to trunk control. Motor control was investigated by measuring trunk kinematics in the frontal plane while manipulating visual availability and introducing a concurrent cognitive task. We examined motor learning on three timescales (within the same trial, minutes), within the same test session (1 h), and between sessions (1 wk). Posture sway was analyzed through time-based measures [root mean square (RMS) sway and RMS velocity], frequency-based measures (amplitude spectra), and parameterized feedback modeling. We found that posture differed in both magnitude and frequency distribution during sway referencing compared with quiet sitting. Modeling indicated that sway referencing caused greater uncertainty/noise in sensory feedback and motor outputs. Sway referencing was also associated with lower active stiffness and damping model parameters. The influence of vision and a cognitive task was more apparent during sway referencing compared with quiet sitting. Short-term learning was reflected by reduced RMS velocity in quiet sitting immediately following sway referencing. Longer term learning was evident from one week to the next, with a 23% decrease in RMS sway and 9% decrease in RMS velocity. These changes occurred predominantly during cognitive tests at lower frequencies and were associated with lower sensory noise and higher stiffness and integral gains in the model. With the findings taken together, the sitting sway-referenced test elicited neural changes consistent with optimal integration and sensory reweighting, similar to standing, and should be a valuable tool to closely examine sensorimotor control of the trunk. NEW & NOTEWORTHY We developed the first sway-referenced system for sitting to highlight the role of vestibular and visual contributions to trunk control. A parametric feedback model explained sensorimotor control and motor learning in the task with and between two test sessions. The sitting sway-referenced test elicited neural changes consistent with optimal integration and sensory reweighting, similar to standing, and should be a valuable tool to closely examine sensorimotor control of the trunk.