Neural asymmetric measurement using non-invasive and non-intrusive multi-modal approach
Creators: name: Bhowmik, Susmit
Publisher: name: RMIT University
Year: 2024
Subjects: classificationCode: 400309
subject: Neural engineering

description: There is a normal and natural asymmetry in the healthy human which changes with age. Changes to this can indicate disease conditions. This work aimed to investigate methods that can measure the lateral asymmetry in the face. 

This thesis has investigated asymmetric facial neural responses to visual stimuli using a multi-modal approach. The activity of facial muscles and the pupil oscillations in reaction to external stimuli were measured. 

My initial observations have shown that facial surface electromyography (fsEMG) signals are often prone to noise contamination due to numerous challenges such as faulty electrode placement and crosstalk from surrounding muscles. Pre-processing of such signals has not been dealt with properly in literature. Hence, I have proposed a pre-processing framework that can enhance the signal quality for further analyses. Ten participants (male/female = 6/4, 23-37 years) were recruited to collect fsEMG data from the corrugator supercilii muscle. A series of muscular movements were performed to incorporate the common noise issues in sEMG signals. Each of the noises was removed effectively using Hampel filtering and adaptive noise cancellation methodologies. The final pre-processed signal has noises removed and an increased SNR by 2.31 dB, and it may also be used for further investigations.

It has been hypothesized that due to bilateral emotion processing in the brain, there are lateral muscular activations on the face since the nerves cross-over at the motor cortex. This asymmetric neural response can be observed through fsEMG during spontaneous emotion elicitation. Another set of experiments were conducted with ten more participants (male/female = 6/4, 23-37 years). The participants watched two positive and two negative videos, while fsEMG signals were recorded from their corrugator supercilii and zygomaticus major muscles.  The signals were pre-processed according to our proposed framework, and root mean square (RMS) and sample entropy (SampEn) analyses were performed. The SampEn values of left and right corrugator during negative emotional stimuli are 0.49±0.1 and 0.52±0.06; again, the SampEn values of left and right zygomaticus during positive emotional stimuli are 0.47±0.1 and 0.48±0.12; with insignificant differences (p&gt;0.05). The corrugator showed higher activations during negative emotion and zygomaticus during positive, but no differences in the hemifacial activations were observed in RMS values either. This work suggested that facial surface electromyography cannot detect facial asymmetry.

The asymmetry hypothesis suggested in the literature was also tested using ocular responses. Pupillary data was recorded using a commercial eye tracker device, and participants were subjected to two different light levels while their pupil behaviour was recorded. Three groups of participants were chosen for the study (1) 30 healthy young (20-35 years), (2) 30 healthy age-matched (58-89 years) and (3) 40 open-angle glaucoma (OAG) patients (62-94 years). Among the glaucoma patients, four patients with unilateral glaucomatous eyes were recruited for a test study.  All participants sat in front of the device at a distance of 65±15 cm, while 34 and 100 cd/m2 light intensities were projected on the eyes for 120 seconds each, respectively. The signals were de-noised using Hampel filter and db2 wavelet transform. 

Approximate entropy was implemented as a pilot entropy analysis and later Sample entropy analysis was implemented to measure the irregularities of the signals. It has been hypothesised, based on the age-complexity theory that with age and disease, complexity of the pupillary data will increase. The results show that the sample entropy values for young, age-matched, and glaucoma have significant differences for both light intensities. 

This study has confirmed that (1) complexity of pupillary data increases with age and diseases (2) it can differentiate affected eyes from healthy eyes in unilateral glaucoma patients (patients who have glaucoma in one of the eyes). Although, neural asymmetry in pupillary responses could not be found but have discovered the application of pupillary responses in detecting glaucoma. The results show that at 100 cd/m2, the sample entropy of the healthy eyes (0.55±0.017) and glaucoma eyes (0.7±0.034) have significant differences (p&lt;0.05). Sample entropy of the hippus oscillations obtained using an eye-tracking device showed a significant difference between glaucoma and healthy eyes and has the potential for being used to detect glaucoma.

The novelty of this work is the association of hippus with age and disease. Sample entropy is useful in differentiating case and control. A portable and inexpensive device has been used for data collection, and the whole method can be completely computerised. Hence, it does not require highly skilled personnel for data collection and ocular dysfunction screening. Despite the limitations of pupillometry, it can be used in ophthalmology clinics and remote areas with limited resources as a tool for ocular neuritis detection. Ideally, in local clinics, a general practitioner (GP) can make use of hippus for visual dysfunction screening.

The study has also shown that this method is suitable for machine supported analysis and thus could be used by nursing or clinical support staff. This could potentially provide extra information to the ophthalmologist, which might be helpful in more complicated diagnoses. Despite the failed asymmetry hypotheses, the work has found a relationship between sample entropy and hippus and reported that with age/disease, pupillary signals tend to be more irregular and jagged. This information can potentially impart knowledge in understanding the ocular control system and help in identifying pathophysiological abnormalities due to ageing and disease.