Real Walking Research Articles

Marker-Less Motion Capture of Insect Locomotion With Deep Neural Networks Pre-trained on Synthetic Videos.

Motion capture of unrestrained moving animals is a major analytic tool in neuroethology and behavioral physiology. At present, several motion capture methodologies have been developed, all of which have particular limitations regarding experimental application. Whereas marker-based motion capture systems are very robust and easily adjusted to suit different setups, tracked species, or body parts, they cannot be applied in experimental situations where markers obstruct the natural behavior (e.g., when tracking delicate, elastic, and/or sensitive body structures). On the other hand, marker-less motion capture systems typically require setup- and animal-specific adjustments, for example by means of tailored image processing, decision heuristics, and/or machine learning of specific sample data. Among the latter, deep-learning approaches have become very popular because of their applicability to virtually any sample of video data. Nevertheless, concise evaluation of their training requirements has rarely been done, particularly with regard to the transfer of trained networks from one application to another. To address this issue, the present study uses insect locomotion as a showcase example for systematic evaluation of variation and augmentation of the training data. For that, we use artificially generated video sequences with known combinations of observed, real animal postures and randomized body position, orientation, and size. Moreover, we evaluate the generalization ability of networks that have been pre-trained on synthetic videos to video recordings of real walking insects, and estimate the benefit in terms of reduced requirement for manual annotation. We show that tracking performance is affected only little by scaling factors ranging from 0.5 to 1.5. As expected from convolutional networks, the translation of the animal has no effect. On the other hand, we show that sufficient variation of rotation in the training data is essential for performance, and make concise suggestions about how much variation is required. Our results on transfer from synthetic to real videos show that pre-training reduces the amount of necessary manual annotation by about 50%.

Effect of a Virtual Reality-Enhanced Exercise and Education Intervention on Patient Engagement and Learning in Cardiac Rehabilitation: Randomized Controlled Trial.

BackgroundCardiac rehabilitation (CR) is clinically proven to reduce morbidity and mortality; however, many eligible patients do not enroll in treatment. Furthermore, many enrolled patients do not complete their full course of treatment. This is greatly influenced by socioeconomic factors but is also because of patients’ lack of understanding of the importance of their care and a lack of motivation to maintain attendance.ObjectiveThis study aims to explore the potential benefits of virtual reality (VR) walking trails within CR treatment, specifically with regard to patient knowledge retention, satisfaction with treatment, and the overall attendance of treatment sessions.MethodsNew CR patients were enrolled and randomized on a rolling basis to either the control group or intervention group. Intervention patients completed their time on the treadmill with VR walking trails, which included audio-recorded education, whereas control patients completed the standard of care therapy. Both groups were assisted by nursing staff for all treatment sessions. Primary outcomes were determined by assessing 6-minute walk test improvement. In addition, secondary outcomes of patients’ cardiac knowledge and satisfaction were assessed via a computer-based questionnaire; patient adherence to the recommended number of sessions was also monitored. Cardiac knowledge assessment included a prerehabilitation education quiz, and the same quiz was repeated at patients’ final visit and again at the 2-month follow-up. The satisfaction questionnaire was completed at the final visit.ResultsBetween January 2018 and May 2019, 72 patients were enrolled—41 in the intervention group and 31 in the control group. On the basis of the results of the prerehabilitation and postrehabilitation 6-minute walk test, no significant differences were observed between the intervention and control groups (P=.64). No statistical differences were observed between groups in terms of education (P=.86) or satisfaction (P=.32) at any time point. The control group had statistically more favorable rates of attendance, as determined by the risk group comparison (P=.02) and the comparison of the rates for completing the minimum number of sessions (P=.046), but no correlation was observed between the study group and reasons for ending treatment.ConclusionsAlthough no improvements were seen in the VR intervention group over the control group, it is worth noting that limitations in the study design may have influenced these outcomes, not the medium itself. Furthermore, the qualitative information suggests that patients may have indeed enjoyed their experience with VR, even though quantitative satisfaction data did not capture this. Further considerations for how and when VR should be applied to CR are suggested in this paper.Trial RegistrationClinicalTrials.gov NCT03945201; https://clinicaltrials.gov/ct2/show/NCT03945201

User-defined walking-in-place gestures for VR locomotion

Locomotion is one of the fundamental interactions in VR. As a relatively easy and simple method to implement VR locomotion, walking-in-place (WIP) techniques have been actively developed, which have shown advantages in terms of spatial constraints and immersion compared to real walking or controller-based interaction. However, existing WIP gestures have been largely adapted or designed from the perspective of developers, not the users, which may result in not only higher cognitive load to learn and memorize, but also worse presence and increased sensory conflict in VR. Therefore, this study aims to elicit and evaluate WIP gestures for different walking directions (forward, sideways, and backward) from users so that a complete user-defined WIP gesture set for VR locomotion can be generated. Two sequential user studies were conducted. In Experiment 1, 20 participants experienced the movement while wearing the VR headset and elicited the gesture for each of 8 walking directions. The grouping analysis revealed that Turn body + Stepping-in-place (SIP) and Step one foot + SIP/Rock/Stay were promising WIP gesture sets for VR locomotion. In the follow-up experiment (Experiment 2), 21 new participants experienced and compared the generated gesture sets and existing ones. The results showed that SIP performed the best for forward walking, while Step one foot + SIP/Rock/Stay were promising for other walking directions, which depended on application scenarios and the tradeoff between efficiency and naturalness. The generated WIP gesture sets from users can be used in VR applications to provide a better user experience and greater movement options in VR locomotion.

An Evaluation Testbed for Locomotion in Virtual Reality

A common operation performed in Virtual Reality (VR) environments is locomotion. Although real walking can represent a natural and intuitive way to manage displacements in such environments, its use is generally limited by the size of the area tracked by the VR system (typically, the size of a room) or requires expensive technologies to cover particularly extended settings. A number of approaches have been proposed to enable effective explorations in VR, each characterized by different hardware requirements and costs, and capable to provide different levels of usability and performance. However, the lack of a well-defined methodology for assessing and comparing available approaches makes it difficult to identify, among the various alternatives, the best solutions for selected application domains. To deal with this issue, this paper introduces a novel evaluation testbed which, by building on the outcomes of many separate works reported in the literature, aims to support a comprehensive analysis of the considered design space. An experimental protocol for collecting objective and subjective measures is proposed, together with a scoring system able to rank locomotion approaches based on a weighted set of requirements. Testbed usage is illustrated in a use case requesting to select the technique to adopt in a given application scenario.

High-Power Density Inertial Energy Harvester Without Additional Proof Mass for Wearables

Inertial energy harvesters have great potential to sustainably power wearable sensors for the Internet of Things. However, the bulky proof mass used to capture kinetic energy limits the power density of such an energy harvester. Targeted for high-power density, we propose an inertial energy harvester without additional proof mass to efficiently scavenge the kinetic energy of human limb swing. By adopting a planetary structure, the power generation unit, comprising the base, coils, rotor, and magnets, serves as an eccentric weight of the system, so no additional proof mass is needed. Excited by limb swing, the power generation unit oscillates along the sun gear so that the rotor is actuated by the sun gear to spin and produce electricity. We build a theoretical model to predict the average output power under limb swing excitations. We fabricate a miniature prototype to experimentally characterize the energy harvester under pseudowalking excitation and evaluate its performance in real walking. The results show that the prototype generates a maximum power of 1.46 mW and power density of $454.82~{\mu }\text{W}$ /cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> in pseudowalking testing, which are over ten times those of its counterparts. In the real walking test, the prototype performed even better, achieving 1.84 and 2.95 mW when worn on the wrist and ankle, respectively. After power regulation, the energy harvester can fully power a pedometer at various walking speeds. Finally, simulations using real walking data demonstrate that the proposed device reaches higher power density compared with conventional structures and that introducing the additional proof mass unnecessarily increases power density.

Virtual reality training platform for a computer numerically controlled grinding machine tool

In-depth training of machine tool (MT) operators is crucial to avoid machine damage due to faulty operation. However, machine-hours are costly and during the training, the MT is unavailable for regular production purposes. Here, virtual real-size models offer a solution by providing basic operation principles to future operators. In this context, it is yet unknown whether a virtual teaching enhanced by real walking is similar to a real teaching scenario regarding the learning efficiency and long-term memory retention. This paper describes a study comparing the learning efficiency of a virtual training session with traditional instructions on a real MT. The learning success of both training groups is objectively and subjectively assessed on a real MT a week later. In this assessment, the task completion time and the number of errors are recorded. We observed that the virtually taught group slightly outperformed trainees taught in reality regarding both objective measurements.

Acceptance and Usability of Immersive Virtual Reality in Older Adults with Objective and Subjective Cognitive Decline.

Virtual reality (VR) has recently emerged as a promising means for the administration of cognitive training of seniors at risk of dementia. Immersive VR could result in increased engagement and performances; however, its acceptance in older adults with cognitive deficits still has to be assessed. To assess acceptance and usability of an immersive VR environment requiring real walking and active participants' interaction. 58 seniors with mild cognitive impairment (MCI, n = 24) or subjective cognitive decline (SCD, n = 31) performed a shopping task in a virtual supermarket displayed through a head-mounted display. Subjective and objective outcomes were evaluated. Immersive VR was well-accepted by all but one participant (TAM3 positive subscales > 5.33), irrespective of the extent of cognitive decline. Participants enjoyed the experience (spatial presence 3.51±0.50, engagement 3.85±0.68, naturalness 3.85±0.82) and reported negligible side-effects (SSQ: 3.74; q1-q3:0-16.83). The environment was considered extremely realistic, such as to induce potentially harmful behaviors: one participant fell while trying to lean on a virtual shelf. Older participants needed more time to conclude trials. Participants with MCI committed more errors in grocery items' selection and experienced less "perceived control" over the environment. Immersive VR was acceptable and enjoyable for older adults in both groups. Cognitive deficits could induce risky behaviors, and cause issues in the interactions with virtual items. Further studies are needed to confirm acceptance of immersive VR in individuals at risk of dementia, and to extend the results to people with more severe symptoms.

Changes in cerebral blood flow during forward and backward walking with speed misperception generated by virtual reality.

[Purpose] The purpose of this study was to investigate the effect of speed misperception on brain activity, created by a speed difference between actual walking and virtual reality walking videos. [Participants and Methods] The participants were 20 healthy young people. The walking speed in the video was set to 3 km/h to induce an error, while the actual walking speed was 1 km/h. Cerebral blood flow was measured using an optical imaging brain function measurement device. Left and right prefrontal cortices were analyzed using two channels and oxyhemoglobin level change from rest was used as a cerebral blood flow index. A t-test compared the cerebral blood flow dynamics before, during, and after the virtual reality video viewing under forward and backward walking conditions. [Results] Regarding changes in oxyhemoglobin levels during walking after watching the virtual reality video, cerebral blood flow increased especially in the backward walking state, where the difference was large in the right prefrontal cortex. [Conclusion] The backward walking that caused misperception by virtual reality is an extraordinary movement compared to forward walking. Thus, it is necessary to voluntarily adjust the movement by the cerebral cortex, and it is thought that activation of the prefrontal cortex occurs.

Kinematic Gait Adjustments to Virtual Environments on Different Surface Conditions: Do Treadmill and Over-Ground Walking Exhibit Different Adaptations to Passive Virtual Immersion?

Background The aim of this study was to examine the kinematic gait adjustments performed in response to passive and photorealistic virtual reality environment (VRE) demands during over-ground and treadmill walking conditions and determine whether the surface presentation order affects the gait adjustments in response to different VREs. Methods Twenty young participants divided into two groups performed two virtual reality (VR) walking protocols which included two different VREs (snowy and crowded conditions). Group A performed the VR over-ground protocol (four natural walking (NW), seven VR snowy, and seven VR crowded trials) followed by the VR treadmill protocol (four NW, one VR snowy, and one VR crowded trials); Group B performed the VR treadmill protocol (four NW, seven VR snowy, and seven VR crowded trials) followed by the VR over-ground protocol (four NW, one VR snowy, and one VR crowded trials). Center of mass (COM) excursion angles and mediolateral (ML) COM excursions were analyzed and used as outcome measures. Results Group A showed higher COM excursion angles and ML-COM excursion on over-ground VR trials compared to NW trials (p < 0.05), while Group B only showed kinematic changes for the crowded VRE compared to NW trials during the treadmill walking protocol (p < 0.05). Post over-ground exposure, Group A showed greater COM excursion angle and ML-COM excursions on VR trials compared to NW trials during the treadmill walking protocol (p < 0.05). Post treadmill exposure, Group B only showed higher COM excursion angles for the snowy VRE compared to NW trials during the over-ground walking protocol (p < 0.01). Conclusion Results showed that higher kinematic gait adjustments in response to VRE demands were observed during over-ground walking. Additionally, higher sensorimotor responses to VRE demands were observed when the VR protocol was first performed on the over-ground surface and followed by the treadmill walking condition (Group A) compared to the opposite (Group B).

Neural Correlates of Freezing of Gait in Parkinson's Disease: An Electrophysiology Mini-Review.

Freezing of gait (FoG) is a disabling symptom characterized as a brief inability to step or by short steps, which occurs when initiating gait or while turning, affecting over half the population with advanced Parkinson's disease (PD). Several non-competing hypotheses have been proposed to explain the pathophysiology and mechanism behind FoG. Yet, due to the complexity of FoG and the lack of a complete understanding of its mechanism, no clear consensus has been reached on the best treatment options. Moreover, most studies that aim to explore neural biomarkers of FoG have been limited to semi-static or imagined paradigms. One of the biggest unmet needs in the field is the identification of reliable biomarkers that can be construed from real walking scenarios to guide better treatments and validate medical and therapeutic interventions. Advances in neural electrophysiology exploration, including EEG and DBS, will allow for pathophysiology research on more real-to-life scenarios for better FoG biomarker identification and validation. The major aim of this review is to highlight the most up-to-date studies that explain the mechanisms underlying FoG through electrophysiology explorations. The latest methodological approaches used in the neurophysiological study of FoG are summarized, and potential future research directions are discussed.

Attitude Trajectory Optimization to Ensure Balance Hexapod Locomotion.

This paper proposes a simple attitude trajectory optimization method to enhance the walking balance of a large-size hexapod robot. To achieve balance motion control of a large-size hexapod robot on different outdoor terrains, we planned the balance attitude trajectories of the robot during walking and introduced how leg trajectories are generated based on the planned attitude trajectories. While planning the attitude trajectories, high order polynomial interpolation was employed with attitude fluctuation counteraction considered. Constraints that the planned attitude trajectories must satisfy during walking were well-considered. The trajectory of the swing leg was well designed with the terrain attitude considered to improve the environmental adaptability of the robot during the attitude adjustment process, and the trajectory of the support leg was automatically generated to satisfy the demand of the balance attitude trajectories planned. Comparative experiments of the real large-size hexapod robot walking on different terrains were carried out to validate the effectiveness and applicability of the attitude trajectory optimization method proposed, which demonstrated that, compared with the currently developed balance motion controllers, the attitude trajectory optimization method proposed can simplify the control system design and improve the walking balance of a hexapod robot.

Training older adults with virtual reality use to improve collision-avoidance behavior when walking through an aperture

Many older adults perform collision-avoidance behavior either insufficiently (i.e., frequent collision) or inefficiently (i.e., exaggerated behavior to ensure collision-avoidance). The present study examined whether a training system using virtual reality (VR) simulation enhanced older adults’ collision-avoidance behavior in response to a VR image of an aperture during real walking. Twenty-five (n = 13 intervention group and n = 12 control group) older individuals participated. During training, a VR image of walking through an aperture was projected onto a large screen. Participants in the intervention group tried to avoid virtual collision with the minimum body rotation required to walk on the spot through a variety of narrow apertures. Participants in the control group remained without body rotation while walking on the spot through a wide aperture. A comparison between pre-test and post-test performances in the real environment indicated that after the training, significantly smaller body rotation angles were observed in the intervention group. This suggests that the training led participants to modify their behavior to try to move efficiently during real walking. However, although not significant, collision rates also tended to be greater, suggesting that, at least for some participants, the modification required to avoid collision was too difficult. Transfer of the learned behavior using the VR environment to real walking is discussed.

A Graded Exposure, Locomotion-Enabled Virtual Reality App During Walking and Reaching for Individuals With Chronic Low Back Pain: Cohort Gaming Design.

BackgroundChronic low back pain (cLBP) can interfere with daily activities, and individuals with elevated pain-related fear (also known as kinesiophobia or the fear of injury due to movement) can develop worse long-term disability. Graded exposure (GEXP) protocols use successive participation in avoided activities to help individuals overcome fearful movement appraisals and encourage activity. We sought to develop a series of GEXP virtual reality (VR) walking and reaching scenarios to increase the exposure and engagement of people with high kinesiophobia and cLBP.ObjectiveThis study aims to (1) determine GEXP content validity of the VR application and (2) determine the feasibility of individuals with cLBP performing locomotion-enabled physical activities.MethodsWe recruited 13 individuals with cLBP and high pain-related fear to experience six VR modules, which provide progressive movement exposure over three sessions in a 1 week period. At session 1, participants ranked each module by likelihood to avoid and assigned an expected pain and concern for harming their back rating to each module. Participants provided a rating of perceived exertion (RPE) after experiencing each module. To test feasibility, we administered the system usability scale (SUS) and treatment evaluation inventory (TEI) following the final session. In addition, we measured pain and pain-related fear at baseline and follow-up.ResultsThe 12 participants who completed the study period assigned higher avoidance (P=.002), expected pain (P=.002), and expected concern (P=.002) for session 3 modules compared with session 1 modules. RPE significantly increased from session 1 (mean 14.8, SD 2.3) to session 3 (mean 16.8, SD 2.2; P=.009). The VR application showed positive feasibility for individuals with cLBP through acceptable SUS (mean 76.7, SD 13.0) and TEI (mean 32.5, SD 4.9) scores. Neither pain (P=.20) nor pain-related fear (P=.58) changed significantly across sessions.ConclusionsThe GEXP VR modules provided progressive exposure to physical challenges, and participants found the VR application acceptable and usable as a potential treatment option. Furthermore, the lack of significant change for pain and pain-related fear reflects that participants were able to complete the modules safely.

Field Expansion with Multiplexing Prism Glasses Improves Pedestrian Detection for Acquired Monocular Vision.

PurposePatients with acquired monocular vision (AMV) lose vision in the temporal crescent on the side of the blind eye. This visual field loss affects patients’ ability to detect potential hazards in the blind field. Mounting a base-in multiplexing prism (MxP) on the nasal side of the seeing eye can provide true field expansion and enable detection of potential collision hazards. We evaluated the efficacy of the MxP glasses in a virtual reality walking environment.MethodsA three-dimensional printed clip-on MxP holder that can be adjusted for an individual user's facial parameters was developed. Virtual reality walking scenarios were designed to evaluate the effect of MxP field expansion on the detection of a pedestrian approaching from different initial bearing angles and courses. The pedestrian detection rates and response times of 10 participants with simulated AMV (normally sighted participants with one eye patched) and three patients with AMV were measured.ResultsThe MxP provided true field expansion of about 25°. Participants performed significantly better with the MxP than without the MxP in the pedestrian detection task on their blind field, while their seeing field performance was not significantly different.ConclusionsThe MxP glasses for patients with AMV improved the detection of potential collision hazards in the blind field.Translational RelevanceThe MxP with an adjustable clip-on holder may help patients with AMV to decrease the risk of collision with other pedestrians.

Effects of a Workplace-Based Virtual-Run Intervention Among University Employees.

Virtual runs (real running or walking activities using online recording platforms) have been popular in the digital age and could have the potential to promote physical activity (PA) in workplaces. We investigated the effects of a virtual-run intervention (VRI) on PA and body compositions among university employees. A three-phase intervention was conducted over 6 months: 0 (pre-intervention), 1 (during intervention), and 2 (post-intervention). Exercise stages of change were assessed in phases 0 and 2. Body compositions (body weight, body mass index, fat mass, percentage of fat mass, fat-free mass, and percentage of fat-free mass) were assessed in phases 0, 1, and 2. Running and walking times were recorded through a mobile application. Forty-seven participants completed the VRI. The number of participants at the maintenance stage increased from 34.04% in phase 0 (n = 16) to 63.83% in phase 2 (n = 30). None of the changes in body compositions were significant (p > 0.05). The median running and walking time among participants at the maintenance stage was 151.85 (interquartile range, 109.15) min/week. Future research should focus on approaches to improve the efficacy of VRIs and their effects on health outcomes.

MPC-Net: A First Principles Guided Policy Search

We present an Imitation Learning approach for the control of dynamical systems with a known model. Our policy search method is guided by solutions from MPC. Typical policy search methods of this kind minimize a distance metric between the guiding demonstrations and the learned policy. Our loss function, however, corresponds to the minimization of the control Hamiltonian, which derives from the principle of optimality. Therefore, our algorithm directly attempts to solve the optimality conditions with a parameterized class of control laws. Additionally, the proposed loss function explicitly encodes the constraints of the optimal control problem and we provide numerical evidence that its minimization achieves improved constraint satisfaction. We train a mixture-of-expert neural network architecture for controlling a quadrupedal robot and show that this policy structure is well suited for such multimodal systems. The learned policy can successfully stabilize different gaits on the real walking robot from less than 10 min of demonstration data.

Evaluating the user experience of omnidirectional VR walking simulators

Omnidirectional treadmills (ODTs) have been traditionally proposed as a promising solution for users’ navigation in large-scale virtual environments. These mechanical devices enable users to perform locomotive motion with 360-deg freedom, while keeping their position fixed in the physical world. However, most locomotion approaches based on omnidirectional treadmills have presented either high acquisition or maintenance costs, being the capabilities of the general public, or a limited reliability. In this paper, we present a comparative usability and acceptance study with real users evaluating the two most common approaches for the development of this type of Virtual Reality (VR) walking simulators, whether flat-based or bowl-based omnidirectional treadmills. The results of our study indicate that both design alternatives accomplish a similar performance and can be considered as personal, low-cost walking simulators for navigation in virtual environments. Nevertheless, when compared between themselves, the users preferred the bowl-based omnidirectional VR treadmill when following three different selection criteria: overall preference, recommendation, and usefulness. Last, a correlation analysis showed statically significant correspondences among the parameters concerning to the simulation presence, which in turn, are related to the global scores and responses given by the participants of the Virtual Reality experiment.

Bio-Inspired Adaptive Locomotion Control System for Online Adaptation of a Walking Robot on Complex Terrains

Developing a controller that enables a walking robot to autonomously adapt its locomotion to navigate unknown complex terrains is difficult, and the methods developed to address this problem typically require robot kinematics with arduous parameter tuning or machine learning techniques that require several trials or repetitions. To overcome this limitation, in this paper, we present continuous, online, and self-adaptive locomotion control inspired by biological control systems, including neural control and hormone systems. The control approach integrates our existing modular neural locomotion control (MNLC) and a newly introduced artificial hormone mechanism (AHM). While the MNLC can generate various gaits through its modulatory input, the AHM, which replicates the endocrine system, adapts to rapid changes in online walking frequency and gait in response to different complex terrains. The control approach is evaluated on an insect-like hexapod robot with 18 degrees of freedom. We provide the results in three sections. First, we demonstrate the adaptability of the robot with the proposed artificial hormones. Second, we compare the performance of two robots with and without artificial hormones while walking on different complex terrains using three performance indexes (stability, harmony, and displacement). Third, we evaluate real-time online adaptations in the real world through real robot walking on different unknown terrains. The experimental results demonstrate that the robot with the proposed artificial hormones does not require several learning trials to adapt its locomotion. Instead, it can continuously adapt its locomotion online, thereby providing greater success and higher performance than other techniques when walking on all terrains.

Probabilistic Multiple Pedestrian Walking Force Model including Pedestrian Inter‐ and Intrasubject Variabilities

A probabilistic walking load model that accounts for inter‐ and intrasubject variabilities has been developed to generate synthetic vertical load waveforms induced by pedestrians. The mathematical model is based on a comprehensive database of continuously recorded pedestrian walking forces on an instrumented treadmill, having a wide range of walking frequencies. The proposed model is able to replicate temporal and spectral features of real walking forces, which is a significant advantage over conventional Fourier series models. The load model results in more realistic force time histories than previous models, since it incorporates significant components of the spectra that are omitted in Fourier series approaches. The proposed mathematical model can be implemented in vibration serviceability assessment of civil engineering structures, such as building floors and footbridges, to estimate more realistically dynamic structural responses due to people walking.

Long-term gait measurements in daily life: Results from the Berlin Aging Study II (BASE-II).

BackgroundWalking ability is an important prerequisite for activity, social participation and independent living. While in most healthy adults, this ability can be assumed as given, limitations in walking ability occur with increasing age. Furthermore, slow walking speed is linked to several chronic conditions and overall morbidity. Measurements of gait parameters can be used as a proxy to detect functional decline and onset of chronic conditions. Up to now, gait characteristics used for this purpose are measured in standardized laboratory settings. There is some evidence, however, that long-term measurements of gait parameters in the living environment have some advantages over short-term laboratory measurements.MethodsWe evaluated cross-sectional data from an accelerometric sensor worn in a subgroup of 554 participants of the Berlin Aging Study II (BASE-II). Data from the two BASE-II age groups (age between 22–36 years and 60–79 years) were used for the current analysis of accelerometric data for a minimum of two days and a maximum of ten days were available. Real world walking speed, number of steps, maximum coherent distance and total distance were derived as average data per day. Linear regression analyses were performed on the different gait parameters in order to identify significant determinants. Additionally, Mann-Whitney-U-tests were performed to detect sex-specific differences.ResultsAge showed to be significantly associated with real world walking speed and with the total distance covered per day, while BMI contributed negatively to the number of walking steps, maximum coherent distance and total distance walked. Additionally, sex was associated with walking steps. However, R2-values for all models were low. Overall, women had significantly more walking steps and a larger coherent distance per day when compared to men. When separated by age group, this difference was significant only in the older participants. Additionally, walking speed was significantly higher in women compared to men in the subgroup of older people.ConclusionsAge- and sex-specific differences have to be considered when objective gait parameters are measured, e.g. in the context of clinical risk assessment. For this purpose normative data, differentiating for age and sex would have to be established to allow reliable classification of long-term measurements of gait.