title: Electromyography based gesture decoding employing few-shot learning, transfer learning, and training from scratch

authors: Godoy, Richardo V.

subjects: artificial intelligence

abstract: Over the last decade several machine learning (ML) based data-driven approaches have been used for Electromyography (EMG) based control of prosthetic hands. However, the performance of EMG-based frameworks can be affected by: i) the onset of fatigue due to long data collection sessions, ii) musculoskeletal differences between individuals, and iii) sensor position drifting between different sessions with the same user. To evaluate these aspects, in this work, we compare the performance of EMG-based hand gesture decoding models developed using three approaches. This comparison allows for future works in EMG-based Human-Machine Interfaces development to make more informed ML decisions. First, we trained from scratch a Transformer-based architecture, called Temporal Multi-Channel Vision Transformer (TMC-ViT). For our second approach, we utilized a pre-trained and fine-tuned TMC-ViT model (a transfer learning approach). Finally, for our third approach, we developed a Prototypical Network (a few-shot learning approach). The models are trained in a subject-specific and subject-generic manner for eight subjects and validated employing the 10-fold cross-validation procedure. This study shows that training a deep learning decoding model from scratch in a subject-specific manner leads to higher decoding accuracies when a larger dataset is available. For smaller datasets, subject-generic models, or inter-session models, the few-shot learning approach produces more robust results with better performance, and is more suited to applications where long data collection scenarios are not possible, or where multiple users are intended for the interface. Our findings show that the few-shot learning approach can outperform training a model from scratch in different scenarios.

text: Electromyography based gesture decoding employing few-shot learning, transfer learning, and training from scratch Over the last decade several machine learning (ML) based data-driven approaches have been used for Electromyography (EMG) based control of prosthetic hands. However, the performance of EMG-based frameworks can be affected by: i) the onset of fatigue due to long data collection sessions, ii) musculoskeletal differences between individuals, and iii) sensor position drifting between different sessions with the same user. To evaluate these aspects, in this work, we compare the performance of EMG-based hand gesture decoding models developed using three approaches. This comparison allows for future works in EMG-based Human-Machine Interfaces development to make more informed ML decisions. First, we trained from scratch a Transformer-based architecture, called Temporal Multi-Channel Vision Transformer (TMC-ViT). For our second approach, we utilized a pre-trained and fine-tuned TMC-ViT model (a transfer learning approach). Finally, for our third approach, we developed a Prototypical Network (a few-shot learning approach). The models are trained in a subject-specific and subject-generic manner for eight subjects and validated employing the 10-fold cross-validation procedure. This study shows that training a deep learning decoding model from scratch in a subject-specific manner leads to higher decoding accuracies when a larger dataset is available. For smaller datasets, subject-generic models, or inter-session models, the few-shot learning approach produces more robust results with better performance, and is more suited to applications where long data collection scenarios are not possible, or where multiple users are intended for the interface. Our findings show that the few-shot learning approach can outperform training a model from scratch in different scenarios.

year: 2023-09-27

title: Further studies on the dialkylation chemistry of [Pt₂(μ-S)₂(PPh₃)₄] with activated alkyl halides RC(O)CH₂X (X = Cl, Br)

authors: Ujam, Oguejiofo Theophilus

subjects: Dinuclear platinum complexes

abstract: Further studies have been carried out into the reactivity of [Pt₂(μ-S)₂(PPh₃)₄] towards a range of activated alkylating agents of the type RC(O)CH₂X (R = organic moiety e.g. phenyl, pyrenyl; X = Cl, Br). Alkylation of both sulfide centres is observed for PhC(O)CH₂Br, 3-(bromoacetyl)coumarin [CouC(O)CH₂Br], and 1-(bromoacetyl)pyrene [PyrC(O)CH2Br], giving dications [Pt₂{μ-SCH₂C(O)R}₂ (PPh₃)₄] ²⁺, isolated as their PF₆⁻ salts. The X-ray structure of [Pt₂{μ-SCH₂C(O)Ph}₂ (PPh₃)₄](PF₆) ₂ shows the presence of short Pt•••O contacts. In contrast, the corresponding chloro compounds [typified by PhC(O)CH₂Cl] and imino analogues [e.g. PhC(NOH)CH₂Br] do not dialkylate [Pt₂ (μ-S)₂(PPh₃)₄]. The ability of PhC(O)CH₂Br to dialkylate [Pt₂(μ-S)₂(PPh₃)₄] allows the synthesis of new mixed-alkyl dithiolate derivatives of the type [Pt₂{μ-SCH₂C(O)Ph}(μ-SR)(PPh₃)₄]²⁺ (R = Et or n-Bu), through alkylation of in situ-generated monoalkylated compounds [Pt₂(μ-S)(μ-SR)(PPh₃)₄]⁺ (from [Pt₂(μ-S)₂(PPh₃)₄] and excess RBr). In these heterodialkylated systems ligand replacement of PPh₃ occurs by the bromide ions in the reaction mixture forming monocations [Pt₂{μ-SCH₂C(O)Ph}(μ-SR)(PPh₃)₃Br]⁺. This ligand substitution can be easily suppressed by addition of PPh₃ to the reaction mixture. The complex [Pt₂{μ-SCH₂C(O)Ph}(μ-SBu)(PPh₃)₄]²⁺ was crystallographically characterised. X-ray crystal structures of the bromide-containing complexes [Pt₂{μ-SCH₂C(O)Ph}(μ-SR)(PPh₃)₃Br]+ (R = Et, Bu) are also reported. In both structures the coordinated bromide is trans to the SCH₂C(O)Ph ligand, which adopts an axial position, while the ethyl and butyl substituents adopt equatorial positions, in contrast to the structures of the dialkylated complexes [Pt₂{μ-SCH₂C(O)Ph}₂(PPh₃)₄]²⁺ and [Pt₂{μ-SCH₂C(O)Ph}(μ-SBu)(PPh₃)₄]²⁺ (and many other known analogues) where both alkyl groups adopt axial positions.

text: Further studies on the dialkylation chemistry of [Pt₂(μ-S)₂(PPh₃)₄] with activated alkyl halides RC(O)CH₂X (X = Cl, Br) Further studies have been carried out into the reactivity of [Pt₂(μ-S)₂(PPh₃)₄] towards a range of activated alkylating agents of the type RC(O)CH₂X (R = organic moiety e.g. phenyl, pyrenyl; X = Cl, Br). Alkylation of both sulfide centres is observed for PhC(O)CH₂Br, 3-(bromoacetyl)coumarin [CouC(O)CH₂Br], and 1-(bromoacetyl)pyrene [PyrC(O)CH2Br], giving dications [Pt₂{μ-SCH₂C(O)R}₂ (PPh₃)₄] ²⁺, isolated as their PF₆⁻ salts. The X-ray structure of [Pt₂{μ-SCH₂C(O)Ph}₂ (PPh₃)₄](PF₆) ₂ shows the presence of short Pt•••O contacts. In contrast, the corresponding chloro compounds [typified by PhC(O)CH₂Cl] and imino analogues [e.g. PhC(NOH)CH₂Br] do not dialkylate [Pt₂ (μ-S)₂(PPh₃)₄]. The ability of PhC(O)CH₂Br to dialkylate [Pt₂(μ-S)₂(PPh₃)₄] allows the synthesis of new mixed-alkyl dithiolate derivatives of the type [Pt₂{μ-SCH₂C(O)Ph}(μ-SR)(PPh₃)₄]²⁺ (R = Et or n-Bu), through alkylation of in situ-generated monoalkylated compounds [Pt₂(μ-S)(μ-SR)(PPh₃)₄]⁺ (from [Pt₂(μ-S)₂(PPh₃)₄] and excess RBr). In these heterodialkylated systems ligand replacement of PPh₃ occurs by the bromide ions in the reaction mixture forming monocations [Pt₂{μ-SCH₂C(O)Ph}(μ-SR)(PPh₃)₃Br]⁺. This ligand substitution can be easily suppressed by addition of PPh₃ to the reaction mixture. The complex [Pt₂{μ-SCH₂C(O)Ph}(μ-SBu)(PPh₃)₄]²⁺ was crystallographically characterised. X-ray crystal structures of the bromide-containing complexes [Pt₂{μ-SCH₂C(O)Ph}(μ-SR)(PPh₃)₃Br]+ (R = Et, Bu) are also reported. In both structures the coordinated bromide is trans to the SCH₂C(O)Ph ligand, which adopts an axial position, while the ethyl and butyl substituents adopt equatorial positions, in contrast to the structures of the dialkylated complexes [Pt₂{μ-SCH₂C(O)Ph}₂(PPh₃)₄]²⁺ and [Pt₂{μ-SCH₂C(O)Ph}(μ-SBu)(PPh₃)₄]²⁺ (and many other known analogues) where both alkyl groups adopt axial positions.

year: 2011

title: Ngā maihi o Te Whare Hukahuka, ngā maihi o Te Whare o Ruamano: Te whare kōrero o ngā maihi o Tuteao

authors: Hona, Hakahaka Charlie Barlow

subjects: Tuteao

abstract: Ko Pūtauaki te maunga
Ko Rangitāiki te awa
Ko Hekerangi te papa whenua
Ko Tuteao te marae
Ko Ngā Maihi te hapū
Ko Ngāti Awa te iwi
Ko Mataatua te waka
Tihe mauri-ora
Ko tōku kāwai rangatira tēnei. E mōhio ai te tangata ko wai ahau; nō hea ahau, nā wai hoki ahau. Ā, nā whai anō taku urupounamu, ko wai a Ngā Maihi o Tuteao? E mea ana ngā pākeke, he iwi tawhito a Ngā Maihi i heke mai i ngā tātai whakapapa o Tangaroa, o Pōtiki, o Mahutapoanui, o Toroa, o Tuteao. Hēoi, kua kore e rangona ōna kōrero i runga marae ātea. Kua kore e wānangahia i roto i te poho o te whare o Tuteao. Kua ngū ngā poupou o te whare kōrero. Ka mutu, i roto i ngā tau tata nei kua riro tītapu ngā puna o te kī, ngā whītiki o te kupu, o te hapū; kua kore e rangona ngā kōrero o Ngā Maihi i runga marae ātea. Ko te haumate o te reo i runga o Tuteao tētahi take i pēnei ai. Nō reira, kai te imu te ruhi, kai te imu te ngēngē. E noho pōhara ana a Ngā Maihi ki ngā tāonga o tōna whare kōrero. Hei te tau 2027, ka whakanuia te rautau o te whare tīpuna a Tuteao, ā i tēnei tau tonu 2022, e whai whakaaro ana te hapū ki taua kaupapa otirā ki te hanga whare tīpuna hou; he whare kaitā e uru ai te tokomaha. Nō reira, e whakaaro ana hoki ki ngā kōrero ka whakairohia ki ngā pakitara o te whare. I tēnei tau hoki kua mana te whakaako i ngā kōrero hītori o te Māori i roto i ngā kura, nō reira he aha rā ngā kōrero e wātea ana ki ngā tamariki o ngā kura e pā ana ki a Ngā Maihi? He maramara, he kongakonga, he putunga kōrero e noho marara ana i ngā wāhi tūmatanui. He uaua te kitea o ētahi atu, kei ngā wāhi tūmataiti, pēnei i te Kōti Whenua Māori, i ngā tuhinga ā-whānau, kei ngā pukapuka wānanga o te marae. Nō reira, he uaua te kite atu i tōna whānuitanga, i tōna hohonutanga. Tīmata ake i ngā kohinga kōrero o te hapū tonu o Ngā Maihi, i ōna kaumātua, i ōna wānanga, i ōna whānau. I tua atu i wā te whare pukapuka, kei ngā wāhi tūmataiti ētahi putunga kōrero hei ō mo te whare kōrero o Ngā Maihi o Tuteao. Ka mutu, kei ngā waiata, ngā haka, ngā mōteatea. Kai ngā kōrero hoki o iwi kē, e pā ana ki wō mātou tīpuna. I reira i tōtō mai i te kōrero.

text: Ngā maihi o Te Whare Hukahuka, ngā maihi o Te Whare o Ruamano: Te whare kōrero o ngā maihi o Tuteao Ko Pūtauaki te maunga
Ko Rangitāiki te awa
Ko Hekerangi te papa whenua
Ko Tuteao te marae
Ko Ngā Maihi te hapū
Ko Ngāti Awa te iwi
Ko Mataatua te waka
Tihe mauri-ora
Ko tōku kāwai rangatira tēnei. E mōhio ai te tangata ko wai ahau; nō hea ahau, nā wai hoki ahau. Ā, nā whai anō taku urupounamu, ko wai a Ngā Maihi o Tuteao? E mea ana ngā pākeke, he iwi tawhito a Ngā Maihi i heke mai i ngā tātai whakapapa o Tangaroa, o Pōtiki, o Mahutapoanui, o Toroa, o Tuteao. Hēoi, kua kore e rangona ōna kōrero i runga marae ātea. Kua kore e wānangahia i roto i te poho o te whare o Tuteao. Kua ngū ngā poupou o te whare kōrero. Ka mutu, i roto i ngā tau tata nei kua riro tītapu ngā puna o te kī, ngā whītiki o te kupu, o te hapū; kua kore e rangona ngā kōrero o Ngā Maihi i runga marae ātea. Ko te haumate o te reo i runga o Tuteao tētahi take i pēnei ai. Nō reira, kai te imu te ruhi, kai te imu te ngēngē. E noho pōhara ana a Ngā Maihi ki ngā tāonga o tōna whare kōrero. Hei te tau 2027, ka whakanuia te rautau o te whare tīpuna a Tuteao, ā i tēnei tau tonu 2022, e whai whakaaro ana te hapū ki taua kaupapa otirā ki te hanga whare tīpuna hou; he whare kaitā e uru ai te tokomaha. Nō reira, e whakaaro ana hoki ki ngā kōrero ka whakairohia ki ngā pakitara o te whare. I tēnei tau hoki kua mana te whakaako i ngā kōrero hītori o te Māori i roto i ngā kura, nō reira he aha rā ngā kōrero e wātea ana ki ngā tamariki o ngā kura e pā ana ki a Ngā Maihi? He maramara, he kongakonga, he putunga kōrero e noho marara ana i ngā wāhi tūmatanui. He uaua te kitea o ētahi atu, kei ngā wāhi tūmataiti, pēnei i te Kōti Whenua Māori, i ngā tuhinga ā-whānau, kei ngā pukapuka wānanga o te marae. Nō reira, he uaua te kite atu i tōna whānuitanga, i tōna hohonutanga. Tīmata ake i ngā kohinga kōrero o te hapū tonu o Ngā Maihi, i ōna kaumātua, i ōna wānanga, i ōna whānau. I tua atu i wā te whare pukapuka, kei ngā wāhi tūmataiti ētahi putunga kōrero hei ō mo te whare kōrero o Ngā Maihi o Tuteao. Ka mutu, kei ngā waiata, ngā haka, ngā mōteatea. Kai ngā kōrero hoki o iwi kē, e pā ana ki wō mātou tīpuna. I reira i tōtō mai i te kōrero.

year: 2022