GangKlang

Hajinejad, Nassrin; Vatterrott, Heide-Rose; Grüter, Barbara; Bogutzky, Simon

doi:10.1145/2544114.2544130

Cited by 4 publications

(2 citation statements)

References 14 publications

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“…Based on this data, various gait parameters (e.g., step length, segment angle, and segment velocity) are computed as output. This output can also be directly converted into acoustic real-time feedback, which has been previously realized in other settings [7,8,10,[41][42][43].…”

Section: Introductionmentioning

confidence: 99%

Sofigait—A Wireless Inertial Sensor-Based Gait Sonification System

Linnhoff

Ploigt

Mattes

2022

Sensors

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In this study, a prototype of an inertial sensor-based gait sonification system was tested for the purpose of providing real-time gait feedback on the knee angle. The study consisted of two parts: (1) a comparison of the knee angle measurement to a marker-based 3D optical capturing system (Vicon, Oxford, UK) with N = 24 participants and (2) an evaluation four different sonification feedback versions in an accentuation × pitch (2 × 2) design on a sample of N = 28 participants. For the measurement system comparison, the RMSE was 7.6° ± 2.6° for the left and 6.9° ± 3.1° for the right side. Measurement agreement with bias up to −7.5° ± 6.2° (for maximum knee flexion) was indicated by the Bland–Altmann Method. The SPM revealed significant differences between both measurement systems for the area 45–90% (p < 0.001) (left) and the area between 45% and 80% (p = 0.007) (right). For the sonification perception, the variation of pitch had a significant effect on the perception of pleasantness of the sound. No effect was found for the accentuation of the swing or stance phase.

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Section: Introductionmentioning

confidence: 99%

Sofigait—A Wireless Inertial Sensor-Based Gait Sonification System

Linnhoff

Ploigt

Mattes

2022

Sensors

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“…Our research activities are organized in three interconnected strands a) process-oriented modeling of walking, b) searching for implicit indices of flow while walking and running and c) supporting (flow-) experiences while walking (Hajinejad et al 2013)). Within the second strand, we searched for candidates for an implicit measurement method of flow-experience while walking and running.…”

mentioning

confidence: 99%

PsychoPhysioCollector: A Smartphone-Based Data Collection App for Psychophysiological Research

Bogutzky¹,

Schrader²,

Hajinejad³

et al. 2016

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Flow is widely understood as a source of creativity and innovation, physical and mental peak performances, and wellbeing. Individuals who experience flow tend to find the activity enjoyable and intrinsically rewarding (Csikszentmihalyi, Abuhamdeh, and Nakamura 2005). In the research project "Flow-Machines: Body Movement and Sound" (2012-2015) funded by German Federal Ministry of Education and Research (BMBF) we addressed how flow while walking can be supported by means of mobile technology. Using the rewarding effect of flow on the future motivation to walk, Flow-Machines should help to change the sedentary lifestyle.

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