Using dynamic point light display stimuli to assess gesture deficits in schizophrenia

Pavlidou, Anastasia; Chapellier, Victoria; Maderthaner, Lydia; Känel, Sofie von; Walther, Sebastian

doi:10.1016/j.scog.2022.100240

Cited by 4 publications

(7 citation statements)

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“…In an event related design, participants will be presented with 30 gestures in a random order: 10 meaningless (e.g., “raise your thumb and your index finger”), 10 meaningful gestures (e.g., “wave good-bye”) and 10 control sentences with no gesture performance expected (e.g., “the weather is bad”). Second, we will use the Postural Knowledge Task (PKT) ( 15 , 26 , 80 ) to assess participants’ gesture perception. Participants will be presented with pictures of people performing gestures (20 trials), while the hands executing those gestures are missing.…”

Section: Methodsmentioning

confidence: 99%

“…Here, human biological movements will be depicted by 12 point-light dots on the main joints of a human actor in the absence of any other visual characteristics (83)(84)(85). For our task, 40 videos of one PLD agent will be shown to perform different communicative gestures while the other PLD agent imitated/followed these performed gestures (26,86). Participants' task will be to identify which PLD was imitating/following the other.…”

Section: Functional Magnetic Resonance Imaging and Tasksmentioning

confidence: 99%

“…Gesture deficits are prevalent in approximately two-thirds of patients with schizophrenia ( 17 , 18 , 23 ). Accumulating evidence suggests that various domains of gesturing are impaired in schizophrenia, including use of gestures ( 17 , 18 , 24 , 25 ) and gesture perception ( 26 ). In fact, individuals with schizophrenia often use incoherent and fewer gestures ( 17 , 27 , 28 ) and tend to interpret gestures negatively ( 29 , 30 ).…”

Section: Introductionmentioning

confidence: 99%

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Brain Stimulation and Group Therapy to Improve Gesture and Social Skills in Schizophrenia—The Study Protocol of a Randomized, Sham-Controlled, Three-Arm, Double-Blind Trial

et al. 2022

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An important component of nonverbal communication is gesture performance, which is strongly impaired in 2/3 of patients with schizophrenia. Gesture deficits in schizophrenia are linked to poor social functioning and reduced quality of life. Therefore, interventions that can help alleviate these deficits in schizophrenia are crucial. Here, we describe an ongoing randomized, double-blind 3-arm, sham-controlled trial that combines two interventions to reduce gesture deficits in schizophrenia patients. The combined interventions are continuous theta burst stimulation (cTBS) and social cognitive remediation therapy (SCRT). We will randomize 72 patients with schizophrenia spectrum disorders in three different groups of 24 patients. The first group will receive real cTBS and real SCRT, the second group will receive sham cTBS and real SCRT, and finally the third group will receive sham SCRT. Here, the sham treatments are, as per definition, inactive interventions that mimic as closely as possible the real treatments (similar to placebo). In addition, 24 age- and gender-matched controls with no interventions will be added for comparison. Measures of nonverbal communication, social cognition, and multimodal brain imaging will be applied at baseline and after intervention. The main research aim of this project will be to test whether the combination of cTBS and SCRT improves gesture performance and social functioning in schizophrenia patients more than standalone cTBS, SCRT or sham psychotherapy. We hypothesize that the patient group receiving the combined interventions will be superior in improving gesture performance.Clinical Trial Registration[www.ClinicalTrials.gov], identifier [NCT04106427].

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Section: Methodsmentioning

confidence: 99%

Section: Functional Magnetic Resonance Imaging and Tasksmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Brain Stimulation and Group Therapy to Improve Gesture and Social Skills in Schizophrenia—The Study Protocol of a Randomized, Sham-Controlled, Three-Arm, Double-Blind Trial

et al. 2022

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“…Nowadays, the rapid development of artificial intelligence and the Internet of Things (IoT) has brought great changes to people’s lives, and human–machine interaction sets application requirements and research ideas for artificial intelligence and the Internet of Things (IoT). − The technology of how to improve the efficiency of communication between human and machine is the most difficult problem for the researchers to overcome, in which the communication system − connecting human and machine is particularly important. Nowadays, there are two main methods of human–machine interaction: voice–machine interaction − and gesture–machine interaction. − Voice signals contain rich character information on humans and are easy to use, so people can use voice signals to make and realize accurate commands. At present, the main sensors currently used for speech recognition are capacitive sensors, , piezoresistive sensors, , piezoelectric sensors, − and triboelectric sensors. − However, some components in capacitive and piezoresistive sensors, such as conventional commercial microphones, rely on battery charging and are vulnerable to environmental noise.…”

Section: Introductionmentioning

confidence: 99%

Human–Machine Interaction via Dual Modes of Voice and Gesture Enabled by Triboelectric Nanogenerator and Machine Learning

Luo

Yang

et al. 2023

ACS Appl. Mater. Interfaces

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With the development of science and technology, human− machine interaction has brought great benefits to the society. Here, we design a voice and gesture signal translator (VGST), which can translate natural actions into electrical signals and realize efficient communication in human−machine interface. By spraying silk protein on the copper of the device, the VGST can achieve improved output and a wide frequency response of 20−2000 Hz with a high sensitivity of 167 mV/dB, and the resolution of frequency detection can reach 0.1 Hz. By designing its internal structure, its resonant frequency and output voltage can be adjusted. The VGST can be used as a high-fidelity platform to effectively recover recorded music and can also be combined with machine learning algorithms to realize the function of speech recognition with a high accuracy rate of 97%. It also has good antinoise performance to recognize speech correctly even in noisy environments. Meanwhile, in gesture recognition, the triboelectric translator is able to recognize simple hand gestures and to judge the distance between hand and the VGST based on the principle of electrostatic induction. This work demonstrates that triboelectric nanogenerator (TENG) technology can have great application prospects and significant advantages in human−machine interaction and high-fidelity platforms.

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“…and execute socially relevant cues (4). In recent years, gestures serve as an important research tool in understanding social communication deficits in schizophrenia patients (5,6).…”

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confidence: 99%

Using virtual reality to assess gesture performance deficits in schizophrenia patients

et al. 2023

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IntroductionGesture performance deficits are prevalent in schizophrenia patients and are strongly associated with poor social communication skills and community functioning, affecting their overall quality of life. Currently, video-recording technology is widely used in clinical settings to assess gesture production deficits in schizophrenia patients. Nevertheless, the subjective evaluation of video-recordings can encumber task assessment. The present study will aim to use virtual reality to examine its potential use as an alternative tool to objectively measure gesture performance accuracy in schizophrenia patients and healthy controls.MethodsGesture performance in the virtual reality setting will be based on the well-established Test of Upper Limb Apraxia. Participants will be immersed in a virtual environment where they will experience themselves being embodied in a collocated virtual body seen from a first-person perspective. Motion trackers will be placed on participants' hands and elbows to track upper body movements in real-time, and to record gesture movement for later analysis. Participants will see a virtual agent sitting across from them, with a virtual table in between. The agent will perform various types of gestures and the participants' task will be to imitate those gestures as accurately as possible. Measurements from the tracking devices will be stored and analyzed to address gesture performance accuracy across groups.DiscussionThis study aims to provide objective measurements of gesture performance accuracy in schizophrenia patients. If successful, the results will provide new knowledge to the gesture literature and offer the potential for novel therapeutic interventions using virtual reality technologies. Such interventions can improve gesturing and thus advance social communication skills in schizophrenia patients.

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Using dynamic point light display stimuli to assess gesture deficits in schizophrenia

Cited by 4 publications

References 64 publications

Brain Stimulation and Group Therapy to Improve Gesture and Social Skills in Schizophrenia—The Study Protocol of a Randomized, Sham-Controlled, Three-Arm, Double-Blind Trial

Brain Stimulation and Group Therapy to Improve Gesture and Social Skills in Schizophrenia—The Study Protocol of a Randomized, Sham-Controlled, Three-Arm, Double-Blind Trial

Human–Machine Interaction via Dual Modes of Voice and Gesture Enabled by Triboelectric Nanogenerator and Machine Learning

Using virtual reality to assess gesture performance deficits in schizophrenia patients

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