title: Telling “Us” in the “Days Destined to You: Response Life-Telling: Indigenous Oral Autobiography and the Performance of Relation

authors: Mahuika, Nepia

subjects: Arts & Humanities

abstract: This “tau-utuutu” (responsive) protocol feels familiar to me.² My turn to speak, to respond, to share in a conversation with Warren Cariou’s stimulating essay on “Life-Telling,” Indigenous autobiography, and Dovie Thomason. It reminds me of how life-telling, orality, and history, interweave and work in my tribal universe. At home, we take turns speaking. We inherit our words, we respond, carve, and weave new narratives—make them ours. Where I come from, lives are frequently “told,” sung, cried, carved, and performed, through tribal conversations, a chorus of textured tones, sometimes in a grand debate within which our personal and collective pasts, presents, and futures converge and diverge.³ I am glad, then, to be invited, to add my voice to this present discussion. It feels natural . . . normal . . . Native.

text: Telling “Us” in the “Days Destined to You: Response Life-Telling: Indigenous Oral Autobiography and the Performance of Relation This “tau-utuutu” (responsive) protocol feels familiar to me.² My turn to speak, to respond, to share in a conversation with Warren Cariou’s stimulating essay on “Life-Telling,” Indigenous autobiography, and Dovie Thomason. It reminds me of how life-telling, orality, and history, interweave and work in my tribal universe. At home, we take turns speaking. We inherit our words, we respond, carve, and weave new narratives—make them ours. Where I come from, lives are frequently “told,” sung, cried, carved, and performed, through tribal conversations, a chorus of textured tones, sometimes in a grand debate within which our personal and collective pasts, presents, and futures converge and diverge.³ I am glad, then, to be invited, to add my voice to this present discussion. It feels natural . . . normal . . . Native.

year: 2016

title: COVID-19 and blind spaces: Responding to digital (in)accessibility and social isolation during lockdown for blind, deafblind, low vision, and vision impaired persons in Aotearoa New Zealand

authors: Graham, Rebekah Sarah

abstract: In this chapter we, as Indigenous (Māori) and non-Indigenous (Pākehā) academics, practitioners, and disability advocates critically examine the experiences of people who are blind, deafblind, low vision and vision impaired (BLV) during the COVID-19 lockdown of Aotearoa New Zealand. We pay particular attention to the ways in which access (or lack thereof) to digital spaces facilitated experiences of social inclusion (and exclusion). Digital connectivity was heavily relied upon during lockdown in Aotearoa New Zealand to disseminate health information and to connect people socially. The use of digital technologies during lockdown extended the interpersonal space of the home beyond the physicality of the urban home people were confined to, drawing people together across the country and creating a sense of shared experience. However, these experiences were not shared equally across the citizenry. Conversations during lockdown with disability advocates and practitioners working with BLV persons identified that. For example, the government website on COVID19 was initially inaccessible for BLV persons and there were assumptions of digital accessibility and literacy within the domestic space of the home. Taken together, these exacerbated existing inequities for BLV persons, some of whom experience multiple domains of exclusion (for example, Indigenous BLV persons with reduced access to services and for whom English is their second language). Drawing on Lefebvre’s (1991) work on the dialectics of space and Lewin’s (1936/2013) construction of the life-space, we consider the interplay of space and experience with regards to the digital and physical space(s) available and inhabited during the shared social experience of lockdown. We discuss possibilities for co-creating socially inclusive (digital) spaces of belonging that reflect and refract life-space relational connections across social groups. Our reflections on the lockdown experience include opportunities post-pandemic for policy makers and practitioners to address digital accessibility inequities.

text: COVID-19 and blind spaces: Responding to digital (in)accessibility and social isolation during lockdown for blind, deafblind, low vision, and vision impaired persons in Aotearoa New Zealand In this chapter we, as Indigenous (Māori) and non-Indigenous (Pākehā) academics, practitioners, and disability advocates critically examine the experiences of people who are blind, deafblind, low vision and vision impaired (BLV) during the COVID-19 lockdown of Aotearoa New Zealand. We pay particular attention to the ways in which access (or lack thereof) to digital spaces facilitated experiences of social inclusion (and exclusion). Digital connectivity was heavily relied upon during lockdown in Aotearoa New Zealand to disseminate health information and to connect people socially. The use of digital technologies during lockdown extended the interpersonal space of the home beyond the physicality of the urban home people were confined to, drawing people together across the country and creating a sense of shared experience. However, these experiences were not shared equally across the citizenry. Conversations during lockdown with disability advocates and practitioners working with BLV persons identified that. For example, the government website on COVID19 was initially inaccessible for BLV persons and there were assumptions of digital accessibility and literacy within the domestic space of the home. Taken together, these exacerbated existing inequities for BLV persons, some of whom experience multiple domains of exclusion (for example, Indigenous BLV persons with reduced access to services and for whom English is their second language). Drawing on Lefebvre’s (1991) work on the dialectics of space and Lewin’s (1936/2013) construction of the life-space, we consider the interplay of space and experience with regards to the digital and physical space(s) available and inhabited during the shared social experience of lockdown. We discuss possibilities for co-creating socially inclusive (digital) spaces of belonging that reflect and refract life-space relational connections across social groups. Our reflections on the lockdown experience include opportunities post-pandemic for policy makers and practitioners to address digital accessibility inequities.

year: 2021

title: Quantification of respiratory sinus arrhythmia by use of low order ARX models

authors: Han, Bo

abstract: Respiratory Sinus Arrhythmia (RSA) is a change in the heart rate that corresponds to the frequency of respiration, but its causative mechanisms in humans remain only partially determined. In this thesis, models of the human cardiovascular system have been developed to give physiologically reasonable explanations of RSA. In a normally intact system, the cardiovascular system has respiration as input and heart rate as the output, which can be used to evaluate the cardiovascular system dynamics. It is proposed that respiration oscillations play a major role in the generation of RSA in healthy humans through the action of medullary respiratory neurons, which have been shown to both control respiration itself and via a coupling to autonomic centers to modulate heart rate by varying parasympathetic and sympathetic inputs to the sinoatrial node. The Baroreflex does not play an important role in modifying the RSA response in normal conditions but does maintain arterial blood pressure within a fairly narrow range through feedback control. Based on the neural network autoregressive with exogenous input (ARX) model, sensitivity analysis has been employed to demonstrate that instantaneous lung volume (ILV) has a much higher percentage of contribution to heart rate variability (HRV) than systolic blood pressure (SBP) (typically 11.6%, 4.6%), which agrees well with our cardiovascular system model.

System identification of RSA in random, regular and spontaneous breathing patterns performed well when using an ARX model of low order, typically [4, 2, x]. In order to get a tradeoff between the accuracy of the model and an excessive number of parameters associated with that model, both the false nearest neighbors (FNN) algorithm and visual inspection of the loss function were used for model order determination. Good model qualities were proved by model validations and agreed well with the results of previous research. Studying transfer characteristics from fluctuations of ILV to HRV, the impulse response was obtained from the ARX model and it was then decomposed algebraically into two combinations of exponential decays, i.e., the fast and slow response components. The low order ARX model was tested on data acquired from a range of healthy subjects and patients.

Analysis of the data indicated that the fast response component of the impulse response corresponds to the high frequency power (HF) (0.3-0.5 Hz) of HRV fluctuations, and the slow response component corresponds to the low frequency power (LF) (0.08-0.15 Hz) of HRV fluctuation. The fast component reflects the change of HRV due to parasympathetic input and the slow component is attributed to both sympathetic and parasympathetic input.

Analysis of the model parameters, the amplitude and time constant of impulse response components, showed these can identify differences in the system response due to the shifts in autonomic balance produced by changing posture and in patients with large sympathetic inputs. Compared with HF:LF power ratio, our slow components of impulse response are more informative in quantifying the balance between the sympathetic and parasympathetic response due to respiration.

To our knowledge, this is first attempt to use an ARX model to quantify RSA for patients in uncontrolled situations where the spontaneous breathing pattern can take on a variety of forms. Our study shows that the results of this system identification to patients are reliable quantitative indexes of RSA after the data has been examined to ensure that cardiorespiratory interaction is linear and stationary.

text: Quantification of respiratory sinus arrhythmia by use of low order ARX models Respiratory Sinus Arrhythmia (RSA) is a change in the heart rate that corresponds to the frequency of respiration, but its causative mechanisms in humans remain only partially determined. In this thesis, models of the human cardiovascular system have been developed to give physiologically reasonable explanations of RSA. In a normally intact system, the cardiovascular system has respiration as input and heart rate as the output, which can be used to evaluate the cardiovascular system dynamics. It is proposed that respiration oscillations play a major role in the generation of RSA in healthy humans through the action of medullary respiratory neurons, which have been shown to both control respiration itself and via a coupling to autonomic centers to modulate heart rate by varying parasympathetic and sympathetic inputs to the sinoatrial node. The Baroreflex does not play an important role in modifying the RSA response in normal conditions but does maintain arterial blood pressure within a fairly narrow range through feedback control. Based on the neural network autoregressive with exogenous input (ARX) model, sensitivity analysis has been employed to demonstrate that instantaneous lung volume (ILV) has a much higher percentage of contribution to heart rate variability (HRV) than systolic blood pressure (SBP) (typically 11.6%, 4.6%), which agrees well with our cardiovascular system model.

System identification of RSA in random, regular and spontaneous breathing patterns performed well when using an ARX model of low order, typically [4, 2, x]. In order to get a tradeoff between the accuracy of the model and an excessive number of parameters associated with that model, both the false nearest neighbors (FNN) algorithm and visual inspection of the loss function were used for model order determination. Good model qualities were proved by model validations and agreed well with the results of previous research. Studying transfer characteristics from fluctuations of ILV to HRV, the impulse response was obtained from the ARX model and it was then decomposed algebraically into two combinations of exponential decays, i.e., the fast and slow response components. The low order ARX model was tested on data acquired from a range of healthy subjects and patients.

Analysis of the data indicated that the fast response component of the impulse response corresponds to the high frequency power (HF) (0.3-0.5 Hz) of HRV fluctuations, and the slow response component corresponds to the low frequency power (LF) (0.08-0.15 Hz) of HRV fluctuation. The fast component reflects the change of HRV due to parasympathetic input and the slow component is attributed to both sympathetic and parasympathetic input.

Analysis of the model parameters, the amplitude and time constant of impulse response components, showed these can identify differences in the system response due to the shifts in autonomic balance produced by changing posture and in patients with large sympathetic inputs. Compared with HF:LF power ratio, our slow components of impulse response are more informative in quantifying the balance between the sympathetic and parasympathetic response due to respiration.

To our knowledge, this is first attempt to use an ARX model to quantify RSA for patients in uncontrolled situations where the spontaneous breathing pattern can take on a variety of forms. Our study shows that the results of this system identification to patients are reliable quantitative indexes of RSA after the data has been examined to ensure that cardiorespiratory interaction is linear and stationary.

year: 1999