Marco Dozza

Auditory biofeedback substitutes for loss of sensory information in maintaining stance

The importance of sensory feedback for postural control in stance is evident from the balance improvements occurring when sensory information from the vestibular, somatosensory, and visual systems is available. However, the extent to which also audio-biofeedback (ABF) information can improve balance has not been determined. It is also unknown why additional artificial sensory feedback is more effective for some subjects than others and in some environmental contexts than others. The aim of this study was to determine the relative effectiveness of an ABF system to reduce postural sway in stance in healthy control subjects and in subjects with bilateral vestibular loss, under conditions of reduced vestibular, visual, and somatosensory inputs. This ABF system used a threshold region and non-linear scaling parameters customized for each individual, to provide subjects with pitch and volume coding of their body sway. ABF had the largest effect on reducing the body sway of the subjects with bilateral vestibular loss when the environment provided limited visual and somatosensory information; it had the smallest effect on reducing the sway of subjects with bilateral vestibular loss, when the environment provided full somatosensory information. The extent that all subjects substituted ABF information for their loss of sensory information was related to the extent that each subject was visually dependent or somatosensory-dependent for their postural control. Comparison of postural sway under a variety of sensory conditions suggests that patients with profound bilateral loss of vestibular function show larger than normal information redundancy among the remaining senses and ABF of trunk sway. The results support the hypothesis that the nervous system uses augmented sensory information differently depending both on the environment and on individual proclivities to rely on vestibular, somatosensory or visual information to control sway.

Audio-biofeedback for balance improvement: an accelerometry-based system

This paper introduces a prototype audio-biofeedback system for balance improvement through the sonification using trunk kinematic information. In tests of this system, normal healthy subjects performed several trials in which they stood quietly in three sensory conditions while wearing an accelerometric sensory unit and headphones. The audio-biofeedback system converted in real-time the two-dimensional horizontal trunk accelerations into a stereo sound by modulating its frequency, level, and left/right balance. Preliminary results showed that subjects improved balance using this audio-biofeedback system and that this improvement was greater the more that balance was challenged by absent or unreliable sensory cues. In addition, high correlations were found between the center of pressure displacement and trunk acceleration, suggesting accelerometers may be useful for quantifying standing balance.

Analysis of Naturalistic Driving Study Data: Safer Glances, Driver Inattention, and Crash Risk

This work was sponsored by the second Strategic Highway Research Program (SHRP 2), which is administered by the Transportation Research Board of the National Academies. This project was managed by Ken Campbell, Chief Program Officer for SHRP 2 Safety , and Jim Hedlund, SHRP 2 Safety Coordinator . The research reported on herein was performed by the main contractor SAFER Vehicle and Traffic Safety Centre at Chalmers, Gothenburg, Sweden. SAFER is a joint research unit where 25 partners from the Swedish automotive industry, academia and authorities cooperate to make a center of excellence within the field of vehicle and traffic safety (see www.chalmers.se/safer ). The host and legal entity SAFER is Chalmers University of Technology. Principle Investigator Tr ent Victor is Adjunct Professor at Chalmers and worked on the project as borrowed personnel to Chalmers but his main employer is Volvo Cars. The other authors of this report are Co - PI Marco Dozza, Jonas Bargman, and Christian - Nils Boda of Chalmers Universi ty of Technology (as a SAFER partner) ; Johan Engstrom and Gustav Markkula of Volvo Group Trucks Technology (as a SAFER partner) ; John D. Lee of University of Wisconsin - Madison (as a consultant to SAFER); and Carol Flannagan of University of Michigan Transp ortation Research Institute (UMTRI) (as a consultant to SAFER). The authors acknowledge the contributions to this research from Ines Heinig, Vera Lisovskaja, Olle Nerman, Holger Rootzen, Dmitrii Zholud, Helena Gellerman , Leyla Vujic, Martin Rensfeldt, Stefan Venbrant, Akhil Krishnan, Bharat Mohan Redrouthu, Daniel Nilsson of Chalmers; Mikael Ljung - Aust of Volvo Cars; Erwin Boer; Christer Ahlstrom and Omar Bagdadi of VTI.

Vibrotactile Biofeedback Improves Tandem Gait in Patients with Unilateral Vestibular Loss

In a crossover design, subjects with unilateral vestibular loss (UVL) practiced tandem gait with eyes closed on two days, two weeks apart, with and without vibrotactile biofeedback (BF) applied to the lateral trunk. Results showed an immediate improvement in postural stability (reduction of lateral center‐of‐mass displacement, trunk tilt, and medial–lateral step width) that was significantly larger than effects of practice alone. However, BF did not increase the rate of improvement or retention of improved stability during gait.

What factors influence drivers' response time for evasive maneuvers in real traffic?

Distraction and inattention contribute to 80% of traffic accidents by delaying or hindering driver responses. However, distraction and inattention are not the only factors increasing response times. In addition, the extent to which different factors-related to the driver, the vehicle, or the environment-influence response times in real traffic is still uncertain. Such knowledge may significantly help the development of countermeasures to distraction and inattention. Naturalistic driving data promises to help determine the causes of distraction and inattention by understanding driver behavior in real traffic. Further, large naturalistic datasets are now publically available from a few sources such as UMTRI (University of Michigan Transportation Institute) and VTTI (Virginia Tech Transportation Institute). However, analysis of such data is made difficult by the intrinsic nature of the data: it is large and complex and the variables of interest are hard to control. This study used the public 100-car and 8-truck naturalistic data from VTTI to show how the NatWare toolkit developed at SAFER (Vehicle and Traffic Safety Center at Chalmers) can be used to determine the influence of several factors on response time. Among these factors, attendance to secondary tasks and eyes-off-road, which are indicators of drivers distraction and inattention, significantly delayed response times; the type of incident and response maneuver also affected response times; and finally, truck drivers responded more quickly than car drivers.

Bio-feedback system for rehabilitation based on a wireless body area network

In this paper we describe bio-WWS, a bio-feedback system for rehabilitation based on dedicated, wireless, sensor-network architecture. The sensor network is designed to be distributed on the users body for balance monitoring and correction. The hardware and software architecture (communication protocols, power management policies and application-level control) have been tuned to optimize cost, battery autonomy and real-time performance required for this application. Bio-WWS is an example of complete vertical integration: the sensor network is fully integrated with processing and auditory feedback generation

Chunking: A procedure to improve naturalistic data analysis

Every year, traffic accidents are responsible for more than 1,000,000 fatalities worldwide. Understanding the causes of traffic accidents and increasing safety on the road are priority issues for both legislators and the automotive industry. Recently, in Europe, the US and Japan, significant public funding has been allocated for performing large-scale naturalistic driving studies to better understand accident causation and the impact of safety systems on traffic safety. The data provided by these naturalistic driving studies has never been available before in this quantity and comprehensiveness and it promises to support a wide variety of data analyses. The volume and variety of the data also pose substantial challenges that demand new data reduction and analysis techniques. This paper presents a general procedure for the analysis of naturalistic driving data called chunking that can support many of these analyses by increasing their robustness and sensitivity. Chunking divides data into equivalent, elementary chunks of data to facilitate a robust and consistent calculation of parameters. This procedure was applied, as an example, to naturalistic driving data from the SeMiFOT study in Sweden and compared with alternative procedures from past studies in order to show its advantages and rationale in a specific example. Our results show how to apply the chunking procedure and how chunking can help avoid bias from data segments with heterogeneous durations (typically obtained from SQL queries). Finally, this paper shows how chunking can increase the robustness of parameter calculation, statistical sensitivity, and create a solid basis for further data analyses.

Energetic assessment of trunk postural modifications induced by a wearable audio-biofeedback system

This paper investigates the trunk postural modifications induced by a wearable device which assesses the trunk sway and provides biofeedback information through sonification of trunk kinematics. The device is based on an inertial wearable sensing unit including three mono-axial accelerometers and three rate gyroscopes embedded and mounted orthogonally. The biofeedback device was tested on nine healthy subjects during quiet stance in different conditions of sensory limitation eyes closed on solid surface, eyes open on foam cushion surface, eyes closed on foam cushion surface. Five trials were performed for each condition; the order of the trials was randomized. The results reported in this paper show how subjects reduced their rotational kinetic energy by using the biofeedback information and how this reduction was related to the limitation of sensory information.

Effects of Linear versus Sigmoid Coding of Visual or Audio Biofeedback for the Control of Upright Stance

Although both visual and audio biofeedback (BF) systems for postural control can reduce sway during stance, a direct comparison between the two systems has never been done. Further, comparing different coding designs of audio and visual BF may help in elucidating how BF information is integrated in the control of posture, and may improve knowledge for the design of innovative BF systems for postural control. The purpose of this paper is to compare the effects of linear versus sigmoid coding of trunk acceleration for audio and visual BF on postural sway in a group of eight, healthy subjects while standing on a foam surface. Results showed that sigmoid-coded audio BF reduced sway acceleration more than did a linear-coded audio BF, whereas a linear-coded visual BF reduced sway acceleration more than a sigmoid-coded visual BF. In addition, audio BF had larger effects on reducing center of pressure (COP) displacement whereas visual BF had larger effects on reducing trunk sway. These results suggest that audio and visual BF for postural control benefit from different types of sensory coding and each type of BF may encourage a different type of postural sway strategy

What is the most effective type of audio-biofeedback for postural motor learning?

Biofeedback is known to improve postural control and reduce postural sway. However, the effects that different biofeedback modes (coding for more or less complex movement information) may have on postural control improvement are still poorly investigated. In addition, most studies do not take into account the effects of spontaneous motor learning from repetition of a task when investigating biofeedback-induced improvement in postural control. In this study, we compared the effects of four different modes of audio-biofeedback (ABF), including direction and/or magnitude of sway information or just a non-specific-direction alarm, on the postural sway of 13 young healthy adults standing on a continuously rotating surface. Compared to the non-specific-direction alarm, ABF of continuous postural sway direction and/or amplitude resulted in larger postural sway reduction in the beginning of the experiment. However, over time, spontaneous postural motor learning flattened the effects of the different modes of ABF so that the alarm was as effective as more complex information about body sway. Nevertheless, motor learning did not make ABF useless, since all modes of ABF further reduced postural sway, even after subjects learned the task. All modes of ABF resulted in improved multi-segmental control of posture and stabilized the trunk-in-space. Spontaneous motor learning also improved multi-segmental control of posture but not trunk-in-space stabilization as much as ABF. In conclusion, although practice standing on a perturbing surface improved postural stability, the more body sway information provided to subjects using ABF, the greater the additional improvement in postural stability.