Ecological Momentary Assessment of Head Motion: Toward Normative Data of Head Stabilization

A Comparison of Walking Behavior during the Instrumented TUG and Habitual Gait

The timed up and go test (TUG) is a common clinical functional balance test often used to complement findings on sensorimotor changes due to aging or sensory/motor dysfunction. The instrumented TUG can be used to obtain objective postural and gait measures that are more sensitive to mobility changes. We investigated whether gait and body coordination during TUG is representative of walking. We examined the walking phase of the TUG and compared gait metrics (stride duration and length, walking speed, and step frequency) and head/trunk accelerations to normal walking. The latter is a key aspect of postural control and can also reveal changes in sensory and motor function. Forty participants were recruited into three groups: young adults, older adults, and older adults with visual impairment. All performed the TUG and a short walking task wearing ultra-lightweight wireless IMUs on the head, chest, and right ankle. Gait and head/trunk acceleration metrics were comparable across tasks. Further, stride length and walking speed were correlated with the participants' age. Those with visual impairment walked significantly slower than sighted older adults. We suggest that the TUG can be a valuable tool for examining gait and stability during walking without the added time or space constraints.

Natural statistics of human head orientation constrain models of vestibular processing

Head orientation relative to gravity determines how gravity-dependent environmental structure is sampled by the visual system, as well as how gravity itself is sampled by the vestibular system. Therefore, both visual and vestibular sensory processing should be shaped by the statistics of head orientation relative to gravity. Here we report the statistics of human head orientation during unconstrained natural activities in humans for the first time, and we explore implications for models of vestibular processing. We find that the distribution of head pitch is more variable than head roll and that the head pitch distribution is asymmetrical with an over-representation of downward head pitch, consistent with ground-looking behavior. We further suggest that pitch and roll distributions can be used as empirical priors in a Bayesian framework to explain previously measured biases in perception of both roll and pitch. Gravitational and inertial acceleration stimulate the otoliths in an equivalent manner, so we also analyze the dynamics of human head orientation to better understand how knowledge of these dynamics can constrain solutions to the problem of gravitoinertial ambiguity. Gravitational acceleration dominates at low frequencies and inertial acceleration dominates at higher frequencies. The change in relative power of gravitational and inertial components as a function of frequency places empirical constraints on dynamic models of vestibular processing, including both frequency segregation and probabilistic internal model accounts. We conclude with a discussion of methodological considerations and scientific and applied domains that will benefit from continued measurement and analysis of natural head movements moving forward.

Natural statistics of human head orientation constrain models of vestibular processing

Head orientation relative to gravity determines how gravity-dependent environmental structure is sampled by the visual system, as well as how gravity itself is sampled by the vestibular system. Therefore, both visual and vestibular sensory processing should be shaped by the statistics of head orientation relative to gravity. Here we report the statistics of human head orientation during unconstrained natural activities in humans for the first time, and we explore implications for models of vestibular processing. We find that the distribution of head pitch is more variable than head roll and that the head pitch distribution is asymmetrical with an over-representation of downward head pitch, consistent with ground-looking behavior. We further show that pitch and roll distributions can be used as empirical priors in a Bayesian framework to explain previously measured biases in perception of both roll and pitch. We also analyze the dynamics of human head orientation to better understand how gravitational and inertial acceleration are processed by the vestibular system. Gravitational acceleration dominates at low frequencies and inertial acceleration dominates at higher frequencies. The change in relative power of gravitational and inertial components as a function of frequency places empirical constraints on dynamic models of vestibular processing. We conclude with a discussion of methodological considerations and scientific and applied domains that will benefit from continued measurement and analysis of natural head movements moving forward.

Natural statistics of head roll: implications for Bayesian inference in spatial orientation

We previously proposed a Bayesian model of multisensory integration in spatial orientation (Clemens IAH, de Vrijer M, Selen LPJ, van Gisbergen JAM, Medendorp WP. J Neurosci 31: 5365-5377, 2011). Using a Gaussian prior, centered on an upright head orientation, this model could explain various perceptual observations in roll-tilted participants, such as the subjective visual vertical, the subjective body tilt (Clemens IAH, de Vrijer M, Selen LPJ, van Gisbergen JAM, Medendorp WP. J Neurosci 31: 5365-5377, 2011), the rod-and-frame effect (Alberts BBGT, de Brouwer AJ, Selen LPJ, Medendorp WP. eNeuro 3: ENEURO.0093-16.2016, 2016), as well as their clinical (Alberts BBGT, Selen LPJ, Verhagen WIM, Medendorp WP. Physiol Rep 3: e12385, 2015) and age-related deficits (Alberts BBGT, Selen LPJ, Medendorp WP. J Neurophysiol 121: 1279-1288, 2019). Because it is generally assumed that the prior reflects an accumulated history of previous head orientations, and recent work on natural head motion suggests non-Gaussian statistics, we examined how the model would perform with a non-Gaussian prior. In the present study, we first experimentally generalized the previous observations in showing that also the natural statistics of head orientation are characterized by long tails, best quantified as a t-location-scale distribution. Next, we compared the performance of the Bayesian model and various model variants using such a t-distributed prior to the original model with the Gaussian prior on their accounts of previously published data of the subjective visual vertical and subjective body tilt tasks. All of these variants performed substantially worse than the original model, suggesting a special value of the Gaussian prior. We provide computational and neurophysiological reasons for the implementation of such a prior, in terms of its associated precision-accuracy trade-off in vertical perception across the tilt range.NEW & NOTEWORTHY It has been argued that the brain uses Bayesian computations to process multiple sensory cues in vertical perception, including a prior centered on upright head orientation which is usually taken to be Gaussian. Here, we show that non-Gaussian prior distributions, although more akin to the statistics of head orientation during natural activities, provide a much worse explanation of such perceptual observations than a Gaussian prior.

The Validity of Wireless Earbud-Type Wearable Sensors for Head Angle Estimation and the Relationships of Head with Trunk, Pelvis, Hip, and Knee during Workouts

The present study was performed to investigate the validity of a wireless earbud-type inertial measurement unit (Ear-IMU) sensor used to estimate head angle during four workouts. In addition, relationships between head angle obtained from the Ear-IMU sensor and the angles of other joints determined with a 3D motion analysis system were investigated. The study population consisted of 20 active volunteers. The Ear-IMU sensor measured the head angle, while a 3D motion analysis system simultaneously measured the angles of the head, trunk, pelvis, hips, and knees during workouts. Comparison with the head angle measured using the 3D motion analysis system indicated that the validity of the Ear-IMU sensor was very strong or moderate in the sagittal and frontal planes. In addition, the trunk angle in the frontal plane showed a fair correlation with the head angle determined with the Ear-IMU sensor during a single-leg squat, reverse lunge, and standing hip abduction; the correlation was poor in the sagittal plane. Our results indicated that the Ear-IMU sensor can be used to directly estimate head motion and indirectly estimate trunk motion.

Evaluation of the Intel RealSense T265 for tracking natural human head motion

Accurate and robust tracking of natural human head motion in natural environments is important for a number of applications including virtual and augmented reality, clinical diagnostics, as well as basic scientific research. IMU provide a versatile solution for recording inertial data including linear acceleration and angular velocity, but reconstructing head position is difficult or impossible. This problem can be solved by incorporating visual data using a technique known as visual-inertial simultaneous localization and mapping (VI-SLAM). A recently released commercial solution, the Intel RealSense T265, uses a proprietary VI-SLAM algorithm to estimate linear and angular position and velocity, but the performance of this device for tracking of natural human head motion in natural environments has not yet been comprehensively evaluated against gold-standard methods. In this study, we used a wide range of metrics to evaluate the performance of the T265 with different walking speeds in different environments, both indoor and outdoor, against two gold-standard methods, an optical tracking system and a so-called perambulator. Overall, we find that performance of the T265 relative to these gold-standard methods is most accurate for slow to normal walking speeds in small- to medium-sized environments. The suitability of this device for future scientific studies depends on the application; data presented here can be useful in making that determination.

Loss of peripheral vestibular input alters the statistics of head movement experienced during natural self-motion

KEY POINTS

Sensory systems are adapted to the statistical structure of natural stimuli, thereby optimizing neural coding. Head motion during natural activities is first sensed and then processed by central vestibulo-motor pathways to influence subsequent behaviour, thereby establishing a feedback loop. To investigate the role of this vestibular feedback on the statistical structure of the head movements, we compared head movements in patients with unilateral vestibular loss and healthy controls. We show that the loss of vestibular feedback substantially alters the statistical structure of head motion for activities that require rapid online feedback control and predict this change by modelling the effects of increased movement variability. Our findings suggest that, following peripheral vestibular loss, changes in the reliability of the sensory input to central pathways impact the statistical structure of head motion during voluntary behaviours.

ABSTRACT

It is widely believed that sensory systems are adapted to optimize neural coding of their natural stimuli. Recent evidence suggests that this is the case for the vestibular system, which senses head movement and contributes to essential functions ranging from the most automatic reflexes to voluntary motor control. During everyday behaviours, head motion is sensed by the vestibular system. In turn, this sensory feedback influences subsequent behaviour, raising the questions of whether and how real-time feedback provided by the vestibular system alters the statistical structure of head movements. We predicted that a reduction in vestibular feedback would alter head movement statistics, particularly for tasks reliant on rapid vestibular feedback. To test this proposal, we recorded six-dimensional head motion in patients with variable degrees of unilateral vestibular loss during standard balance and gait tasks, as well as dynamic self-paced activities. While distributions of linear accelerations and rotational velocities were comparable for patients and age-matched healthy controls, comparison of power spectra revealed significant differences during more dynamic and challenging activities. Specifically, consistent with our prediction, head movement power spectra were significantly altered in patients during two tasks that required rapid online vestibular feedback: active repetitive jumping and walking on foam. Using computational methods, we analysed concurrently measured torso motion and identified increases in head-torso movement variability. Taken together, our results demonstrate that vestibular loss significantly alters head movement statistics and further suggest that increased variability and impaired feedback to internal models required for accurate motor control contribute to the observed changes.

Robust Step Detection from Different Waist-Worn Sensor Positions: Implications for Clinical Studies

Analyzing human gait with inertial sensors provides valuable insights into a wide range of health impairments, including many musculoskeletal and neurological diseases. A representative and reliable assessment of gait requires continuous monitoring over long periods and ideally takes place in the subjects' habitual environment (real-world). An inconsistent sensor wearing position can affect gait characterization and influence clinical study results, thus clinical study protocols are typically highly proscriptive, instructing all participants to wear the sensor in a uniform manner. This restrictive approach improves data quality but reduces overall adherence. In this work, we analyze the impact of altering the sensor wearing position around the waist on sensor signal and step detection. We demonstrate that an asymmetrically worn sensor leads to additional odd-harmonic frequency components in the frequency spectrum. We propose a robust solution for step detection based on autocorrelation to overcome sensor position variation (sensitivity = 0.99, precision = 0.99). The proposed solution reduces the impact of inconsistent sensor positioning on gait characterization in clinical studies, thus providing more flexibility to protocol implementation and more freedom to participants to wear the sensor in the position most comfortable to them. This work is a first step towards truly position-agnostic gait assessment in clinical settings.

Control of Linear Head and Trunk Acceleration During Gait After Unilateral Vestibular Deficits

OBJECTIVE

To use clinically available inertial measurement units to quantify the control of linear accelerations at the head and trunk during gait in different sensory conditions in individuals with unilateral vestibular loss.

DESIGN

Observational study.

SETTING

Outpatient research laboratory.

PARTICIPANTS

Individuals (n=13; mean age, 47.6±13.7y; 69% women) 6 weeks after vestibular schwannoma resection surgery and vestibular healthy participants (n=16; mean age, 29.7±5.9y; 56% women).

INTERVENTION

Not applicable.

MAIN OUTCOME MEASURES

Walking speed normalized, root mean square values of cranial-caudal, medial-lateral, and anterior-posterior directed linear accelerations at the head and the trunk while walking in 2 visual sensory conditions (eyes open and eyes closed).

RESULTS

Linear mixed models for each root mean square value were fit on the effects of group, condition, and group by condition. The group by condition effect was used to examine the primary hypothesis that individuals with vestibular loss would experience greater change in triplanar root mean square values at the head and trunk from the eyes open to eyes closed condition compared with the vestibular healthy group. The group by condition effect was found to be significant at the head in the cranial-caudal (β=0.39; P=.002), medial-lateral (β=0.41; P<.001), and anterior-posterior (β=0.43; P<.001) directions. The group by condition effect was also significant in the cranial-caudal (β=0.39; P=.002), medial-lateral (β=0.39; P<.001), and anterior-posterior (β=0.23; P=.002) directions at the trunk.

CONCLUSIONS

Participants who underwent vestibular schwannoma resection were more impaired in their ability to control accelerations at the head and trunk without visual sensory information than vestibular healthy participants. These impairments were detectable using clinically available inertial measurement units.

Somatosensory Influence on Platform-Induced Translational Vestibulo-Ocular Reflex in Vertical Direction in Humans

The vestibulo-ocular reflex (VOR) consists of two components, the rotational VOR (rVOR) elicited by semicircular canal signals and the translational VOR (tVOR) elicited by otolith signals. Given the relevant role of the vertical tVOR in human walking, this study aimed at measuring the time delay of eye movements in relation to whole-body vertical translations in natural standing position. Twenty (13 females and 7 males) healthy, young subjects (mean 25 years) stood upright on a motor-driven platform and were exposed to sinusoidal movements while fixating a LED, positioned at a distance of 50 cm in front of the eyes. The platform motion induced a vertical translation of 2.6 cm that provoked counteracting eye movements similar to self-paced walking. The time differences between platform and eye movements indicated that the subject's timing of the extraocular motor reaction depended on stimulus frequency and number of repetitions. At low stimulus frequencies (<0.8 Hz) and small numbers of repetitions (<3), eye movements were phase advanced or in synchrony with platform movements. At higher stimulus frequencies or continuous stimulation, eye movements were phase lagged by ~40 ms. Interestingly, the timing of eye movements depended on the initial platform inclination. Starting with both feet in dorsiflexion, eye movements preceded platform movements by 137 ms, whereas starting with both feet in plantar flexion eye movement precession was only 19 ms. This suggests a remarkable influence of foot proprioceptive signals on the timing of eye movements, indicating that the dynamics of the vertical tVOR is controlled by somatosensory signals.